Huygens Remote Manager documentation#

This is the user and system administrator documentation for the Huygens Remote Manager (HRM).

Main sections#

Installation instructions#

These are the detailed installation and administration instructions for the Huygens Remote Manager.

Conventions#

This page lists some conventions and notations used in this documentation.

Using sudo#

Throughout this document, we’re assuming that commands which require root permissions can be issued by using sudo. If your system is not configured for this, you can either login directly as root (considered as “bad practice”) or use the su - command to switch to the root user.

note We highly recommend the usage of sudo though!

Operating systems#

The recommended linux distributions are:

Icon

Distribution name

debian

Debian

ubuntu

Ubuntu

rocky

Rocky Linux

alma

Alma Linux

We will use tabs to group the code and instructions for respective operating system families

Tab name

Corresponding operating system family

Debian

Debian, Ubuntu

RHEL

RedHat, Rocky Linux, Alma Linux

Warning

Please notice that with release 3.1, we dropped support for macosx Mac OS X. HRM 3.0 is still known to work on Mac OS X from 10.5 (Leopard) onward, but no effort will be made to make future versions of the HRM compatible with Mac OS X. Also notice that the HRM was never tested on Mavericks.

Variables#

Variable

Description

(Example) value

$WWW_ROOT

Web server document root

/var/www/html

$HRM_HOME

HRM root (home) folder

$WWW_ROOT/hrm

$HRM_CONFIG

HRM configuration folder

$HRM_HOME/config

$HRM_SAMPLES

HRM configuration samples folder

$HRM_HOME/config/samples

$HRM_RESRC

HRM resources folder

$HRM_HOME/resources

$HRM_SETUP

HRM setup folder

$HRM_HOME/setup

$HRM_BIN

HRM executables folder

$HRM_HOME/bin

$HRM_USER

HRM customization folder

$HRM_HOME/user

$HRM_LOG

HRM logging folder

/var/log/hrm

$HRM_DATA

HRM data folder

/data/hrm_data

If you want to use those variables in your interactive shell later on, just copy-paste the following lines into your session and adjust the values accordingly:

WWW_ROOT=/var/www/html                 # Web server document root
HRM_HOME=$WWW_ROOT/hrm                 # HRM root (home) folder
HRM_CONFIG=$HRM_HOME/config            # HRM configuration folder
HRM_SAMPLES=$HRM_HOME/config/samples   # HRM configuration samples folder
HRM_RESRC=$HRM_HOME/resources          # HRM resources folder
HRM_SETUP=$HRM_HOME/setup              # HRM setup folder
HRM_BIN=$HRM_HOME/bin                  # HRM executables folder
HRM_USER=$HRM_HOME/user                # HRM customization folder
HRM_LOG=/var/log/hrm                   # HRM logging folder
HRM_DATA=/data/hrm_data                # HRM data folder

Automated installation (beta)#

Note

This feature is still considered experimental but greatly simplifies the installation of an HRM website compared to the Manual installation (recommended) instructions. After a final cycle of testing, this method will become the new recommended way to install HRM.

Get the installation script#

github To get the latest release directly from our git repository, run the following in a shell:

$ git clone https://github.com/aarpon/hrm_installer

Basic operation#

The most basic way to run the script to install HRM is to simply launch setup.sh as a priviledge user. In a shell, type the following:

$ sudo ./setup.sh

There are a few prerequisites to take care of before the script is run. In case these are not met, the script will display helpful error messages and abort. You will need:

  • A supported OS. For this release, this means Ubuntu 20.04, Debian 11, Rocky Linux 8.5 or AlmaLinux 8.4 only.

  • The script must be run as a priviledged user, either as root or using sudo.

  • You will need an active Internet connection to clone the HRM repository.

  • Hucore must be installed and a license available.

Further documentation#

For now, the documentation is available on https://github.com/aarpon/hrm_installer and better instructions will be added here later.

Getting help#

If you are interested in this installation method and have any issues you want to discuss, please enquire on the image.sc forum over at https://forum.image.sc/tag/svi-huygens

Note

Version 3.9 requires PHP 8.1 to run!

Note

These instructions always explain the steps required to upgrade from last stable release to current stable release. However, each section also provides links to instructions for older versions.

Version upgrade#

If you have upgraded the HRM in the past, you will know that some steps must be performed in addition to replacing the old HRM code with the new one: some entries might have been added or changed in the configuration files (hrm_config.inc), and the database structure might have been changed.

Stop the Queue Manager#

Significant parts of the configuration as well as the database are usually changed during an upgrade, so the Queue Manager needs to be stopped first.

Shut down the Queue Manager with:

sudo /etc/init.d/hrmd stop

if you are using System-V or upstart, or with:

sudo systemctl stop hrmd.service

if you are using systemd.

In some rare situations, the Queue Manager might get stuck. To ensure the stop command did work properly, run the following check.

On System-V or upstart:

sudo /etc/init.d/hrmd status

On systemd:

sudo systemctl status hrmd.service

Alternatively, you can use:

ps aux | grep -i [r]unHuygens

that should return empty (nothing).

Get the new HRM release#

To install the new HRM version you need to download the .zip file from the website or github as explained in downloading the standard archive.

Warning

Please do not extract the new archive on top of the previous HRM installation! See details below.

Clean up previous installations#

Because of changes in tree structure of the code and of the external dependences (starting from version 3.4), we highly recommend not to extract the new archive on top of the old one.

Please rename the old hrm folder, extract the code into a fresh ${HRM_ROOT} and move the configuration files from the old config subfolder into the new ${HRM_ROOT}/config.

You might also want to reinstall the hrmd or hrmd.service scripts.

Note

Please follow these instructions first if you are upgrading from older versions.

Check the configuration file#

An easy way to check for modifications is by running the $HRM_HOME/resources/checkConfig.php script. From the shell, run:

cd $HRM_HOME
php resources/checkConfig.php config/hrm_config.inc

There were no configuration changes between versions 3.8 and 3.9 of HRM. The output of the checkConfig.php script should be:

Checking against HRM v3.9.
Check completed successfully! Your configuration file is valid!

Please make sure to fix all problems you might have! The sample files and the Manual installation (recommended) instructions will help you set the correct parameters.

Note

Please follow these instructions first if you are upgrading from older versions.

Update the database#

Newer versions of the HRM might use slightly different/updated versions of the database back-end than previous ones.

HRM version

Database version

3.9

20

3.8

19

3.7

18

3.6

17

3.5

16

3.4

15

3.3

14

3.2

13

3.1

12

3.0.3

11

3.0

10

2.1

9

2.0

8

1.2.3

7

For this reason, the first time you run the HRM after an update you will be told that the database must be updated and that you are not allowed to continue until this has been done!

Note

Database updates are supported across HRM versions, i.e. it is possible to upgrade the database from revision 7 to 20 in one step.

The following describes two possible ways to update the database.

Note

Although we test this procedure quite carefully, it is highly recommended to backup the database before updating!

Updating from the web interface#

Login to the HRM as the admin user: you will be brought directly to the Database update page. Click on the update button. If everything works properly (as it should…), the following message should be displayed.

Needed database revision for HRM v3.9 is number 20.
Current database revision is number 19.
Updating...

Database successfully updated to revision 20.

The database is now at the latest revision.

Updating from the console#

Alternatively, the database can be updated from the console (see create or update database). Please pay attention to what the update process will report! The output should be the same as the one listed in the previous section, but if the update fails, you might want to report it.

Check your HRM-OMERO connector#

In case you are using the HRM-OMERO connector, you will need to update that one as well as it has been split into a separate project. Please refer to the instructions on the HRM-OMERO project page for details.

Re-start the Queue Manager#

After processing the described upgrade steps, the Queue Manager needs to be started again, with:

sudo /etc/init.d/hrmd start

if you are using System-V or upstart, or with:

sudo systemctl start hrmd.service

if you are using systemd.

Upgrade from previous releases#

The following pages are linked to from the relevant sections above, but are listed here again for convenience.

Clean up previous installations#

Warning

These instructions refer to older versions of HRM!

3.4 and newer#

It is highly recommended not to extract the new archive on top of the old one.

Please rename the old hrm folder, extract the code into a fresh ${HRM_ROOT} and move the configuration files from the old config subfolder into the new ${HRM_ROOT}/config.

You might also want to reinstall the hrmd or hrmd.service scripts.

3.3 to 3.4#

In version 3.4, we started a major reorganization of the code structure of HRM and it is therefore highly recommended not to extract the new archive on top of the old one.

Please rename the old hrm folder, extract the code into a fresh ${HRM_ROOT} and move the configuration files from the old config subfolder into the new ${HRM_ROOT}/config.

You might also want to reinstall the hrmd or hrmd.service scripts.

3.2 to 3.3#

HRM 3.3 uses new init scripts. Please delete the old files $HRM_BIN/hrm_user_manager, $HRM_BIN/hrm_user_manager_old, $HRM_BIN/hrmd and $HRM_BIN/ome_hrm and then follow the instructions in Upgrade the init script.

Upgrade the init script#

Note

If your Linux installation is using the systemd init system, please have a look at the instructions about how to set up the HRM daemon with systemd. Please make sure to remove the old init script at /etc/init.d/hrmd in this case!

Otherwise, proceed as described here for the init script.

This step is basically identical to the initial installation of the init script as described in installing the daemon. You need to copy the new script from $HRM_RESRC/sysv-init-lsb/hrmd to /etc/init.d/ and make sure it is executable. This can be done using the following commands:

sudo cp -v $HRM_RESRC/sysv-init-lsb/hrmd /etc/init.d/hrmd
sudo chmod +x /etc/init.d/hrmd
Update the data folder permissions#

As of HRM 3.2.0, the system users running the Queue Manager and the web server are expected to have full read-write access to $HRM_DATA. The supported way of doing this is explained in setting up the HRM user and group. Briefly:

  • a user hrm and its corresponding group hrm are created

  • the web server user (ubuntu www-data, RHEL apache) is added to the hrm group

  • the variable SUSER is set to hrm in /etc/hrm.conf

  • the $HRM_DATA and $HRM_LOG group ownership is set to hrm with the setgid bit set

For detailed instructions, please see setting up the HRM user and group.

Warning

With HRM 3.2 it was possible to preserve the old behavior by setting a configuration variable $change_ownership. This is not supported with HRM 3.3 any more!

3.1 to 3.2#
rm -v inc/ActiveDirectory.inc.php inc/Ldap.inc.php
Update configuration files#

Warning

These instructions refer to older versions of HRM!

3.7 to 3.8#

HRM 3.8 brings a few simplifications in the configuration files. Please run the following commands:

cd $HRM_HOME/config
cp -p hrm_server_config.inc hrm_config.inc

Note

The following files have become redundant and can be removed:

$HRM_HOME/config/hrm_server_config.inc

$HRM_HOME/config/hrm_client_config.inc

If you are upgrading from an older version of HRM and both files had the same content, you can simply rename one of them to hrm_config.inc.

3.6 to 3.7#

There were no changes in the configuration files between versions 3.6 and 3.7 of HRM.

3.5 to 3.6#

There were no changes in the configuration files between versions 3.5 and 3.6 of HRM.

3.4 to 3.5#

There were no changes in the configuration files between versions 3.4 and 3.5 of HRM.

3.3 to 3.4#
$authenticateAgainst#

The support for various authentication mechanisms was extended in HRM 3.4. This comes with a change in configuration: the $authenticateAgainst variable is now an array and its values have also changed (although, temporarily, the old ones are still supported). Example:

<?php
...
$authenticateAgainst = array("active_dir", "integrated");
...
$useDESEncryption#

The configuration variable $useDESEncryption (that was not used) must be removed from the configuration files!

Note

Please follow these instructions first if you are upgrading from older versions.

3.2 to 3.3#

The $change_ownership option is not supported in version 3.3 any more. If the variable is present in the configuration files hrm_{server|client}_config.inc it will be silently ignored. For consistency reasons it is therefore recommend to remove this setting from the config file(s).

Group authentication#

As of HRM 3.3, external authentication via Active Directory or generic LDAP now supports group authorization. An additional array $AUTHORIZED_GROUPS can be set to define the set of Active Directory or generic LDAP groups that are granted access to HRM.

3.1 to 3.2#

As of version 3.2 of HRM, the system users running the Queue Manager and the web server are expected to have direct read-write access to the data folders. If this is not the case for your setup and you rely on adding the web server user to /etc/sudoers, please notice that this behavior is deprecated in 3.2 but can still be enabled by adding:

$change_ownership=true;

in hrm_{server|client}_config.inc. The variable $change_ownership defaults to false if not explicitly set to true in the configuration, in compliance to the new behavior.

Note

As of HRM 3.3, this variable will be ignored and the new behavior will be enforced!

3.0.x to 3.1#

No changes in the configuration files.

2.1.x to 3.0#

From HRM 2.1.x to HRM 3.0, one variable was added in the configuration files.

$omero_transfers={true|false}
1.2.x to 2.0#

From HRM 1.2.x to HRM 2.0, three variables were added in the configuration files:

[+] max_upload_limit
[+] max_post_limit
[+] email_list_separator

Moreover, three variables were removed:

[-] resultImagesOwnedByUser
[-] resultImagesRenamed
[-] enable_code_for_huygens

Note

If you are upgrading straight from HRM 1.2.x, please notice that as of HRM 2.0 configuration and sample files were moved as per following table.

Config files (new)

Sample files (new)

Config files (1.x)

Sample files (1.x)

$HRM_HOME/config

$HRM_HOME/config/samples

$HRM_HOME/inc

$HRM_HOME/resources

Check configuration files#

Warning

These instructions refer to older versions of HRM!

An easy way to check for modifications is by running the $HRM_HOME/resources/checkConfig.php script. From the shell, run:

cd $HRM_HOME
php resources/checkConfig.php config/hrm_config.inc
3.7 to 3.8#

Checking the 3.7 files with the 3.8.x checkConfig.php script will result in the following output:

Checking against HRM v3.8.
Check completed successfully! Your configuration file is valid!
3.6 to 3.7#

Checking the 3.6 files with the 3.7.x checkConfig.php script will result in the following output:

Checking against HRM v3.7.
Check completed successfully! Your configuration file is valid!
3.5.x to 3.6#

Checking the 3.5 files with the 3.6.x checkConfig.php script will result in the following output:

Checking against HRM v3.6.x.

* * * Error: variable default_output_format not set or empty.
* * * Error: variable min_free_mem_launch_requirement not set or empty.
Check completed with errors! Please fix your configuration!
3.4.x to 3.5#

Checking the 3.4 files with the 3.5.x checkConfig.php script will result in the following output:

Check against HRM v3.5.x.
Check completed successfully! Your configuration file is valid!
3.3.x to 3.4#

Checking the 3.3 files with the 3.4.x checkConfig.php script will result in the following output:

Check against HRM v3.4.x.
* * * Error: variable useDESEncryption must be removed from the configuration files!
* * * Error: variable 'authenticateAgainst' must be an array!
* * * Moreover, please change 'MYSQL' into 'integrated'.
Check completed with errors! Please fix your configuration!
3.2.x to 3.3#

Checking the 3.2.x files with the 3.3 checkConfig.php script will result in the following output:

Check against HRM v3.3.x.
* * * Error: variable change_ownership must be removed from the configuration files!
Check completed with errors! Please fix your configuration!
3.1.x to 3.2.x#

Checking the 3.1.x files with the 3.2.x checkConfig.php script will result in the following output:

Check against HRM v3.2.x.
Check completed successfully! Your configuration file is valid!
3.0.x to 3.1.x#

Checking the 3.0.x files with the 3.1.x checkConfig.php script will result in the following output:

Check against HRM v3.1.x.
Check completed successfully! Your configuration file is valid!
2.1.x to 3.0.x#

Checking the 2.1.x files with the 3.0 checkConfig.php script will result in the following output:

Check against HRM v3.0.x.
* * * Error: variable omero_transfers not set or empty.
Check completed with errors! Please fix your configuration!
1.2.x to 2.1.x#

Checking the 1.2.x files with the 2.1.x checkConfig.php script will result in the following output:

Check against HRM v2.1.x.
* * * Error: variable max_upload_limit not set or empty.
* * * Error: variable max_post_limit not set or empty.
* * * Error: variable email_list_separator not set or empty.
* * * Error: variable resultImagesOwnedByUser must be removed from the configuration files!
* * * Error: variable resultImagesRenamed must be removed from the configuration files!
* * * Error: variable enable_code_for_huygens must be removed from the configuration files!
Check completed with errors! Please fix your configuration!

Please make sure to fix all problems. The sample files and the Manual installation (recommended) instructions will help you set the correct parameters.

User manual#

These are the detailed instructions for the Huygens Remote Manager User Manual.

Introduction#

The HRM is a collaborative open-source interface to Huygens Core for multi-user, web-based, scheduled, batch deconvolution.

The Huygens Remote Manager (HRM) enables large groups of users to work with Huygens on a central system through an easy-to-use interface. HRM is web-based and therefore easily accessible from your workstation, home PC, tablet or smart phone.

An HRM server can distribute work among several processing machines smartly, which allows for intelligent use of hardware and fast processing times. It features an intelligent queue that switches among the jobs of all users.

HomePanel

Who makes HRM#

HRM is an open source project, this means that the code is freely accessible and it can be adapted and modified to any needs by any user.

HRM is a joined collaboration of Huygens users from:

  • Montpellier RIO Imaging,

  • Facility for Advanced Imaging and Microscopy at the Friedrich Miescher Institute (FMI, Basel),

  • The BioImaging and Optics Platform at the Ecole Polytechnique Fédérale de Lausanne,

  • The Department of Biosystems Science and Engineering at the ETH Zürich,

  • The Leibniz Institute for Neurobiology (Magdeburg),

  • The Combinatorial Neuroimaging facility (Magdeburg),

  • The Imaging Core Facility at the Biozentrum (University of Basel).

  • The University of Fribourg.

  • The Microscopy and Image Analysis Platform of the University of Freiburg.

  • The University of Manchester.

Scientific Volume Imaging participates in this project by contributing its experience in deconvolution and software engineering.

Collaborators

Where to find HRM#

HRM is a free and open source project, and can be found on http://huygens-rm.org. The source code is hosted on https://github.com/aarpon/hrm.

More information about HRM and links to other HRM resources can be found in this online article of the SVI Wiki. Instructions for online testing, downloading and installing HRM are also linked on that page.

Installing HRM on a regular web server is not very difficult. Please consult the Installation instructions and the SVI Wiki.

Getting started#

Here is a quick guide to get you started with the HRM/HuCore deconvolution. In order to optimize results, please refer to section Deconvolution with the HRM.

Select UI theme in HRM#

HRM offers two UI themes (dark, light) that can be selected from the login page.

ThemeChoiceScreenshot

ThemesScreenshot

The theme selected at the moment of logging in is preserved during the entire session. In this manual screenshots from both themes are displayed interchangeably.

Create an account in HRM#

  • If your imaging facility already offers deconvolution via HRM, proceed to the facility’s HRM login page.

  • If HRM is not available at your imaging facility you can still familiarize with HRM by using the HRM demo server offered by SVI.

Follow the registration link on the HRM login page and complete the short form. Names are case sensitive. Upon registration the new HRM account needs to be validated by the administrator.

RegistrationLink RegistrationForm

Upload a raw image#

Upon successful logon the HRM Home panel will be displayed:

HomePanel

To upload images click on the Raw images icon RawImages22x22. The following, intuitive upload tool allows for multiple uploads from your local device:

UploadFiles

Deconvolve#

To submit a deconvolution job proceed to Launch jobs StartJob22x22 from the home panel. The process of submitting the job is split into the following 5 steps:

  • SelectImages48x48 Step 1/5 - Select images: click on the “Image File Format” drop down widget to select the file type of the images to deconvolve. All uploaded files of that format will belisted. Use the DownArrow22x22 UpArrow22x22 icons to add/remove images to/from the selection. When selecting a file, a preview can be generated by using the link GeneratePreviewLink on the right hand side panel. The image preview also contains information about the dimensions, sampling and number of channels.

  • ImageParameters48x48 Step 2/5 - Image parameters: A parameter template describing the imaging conditions of acquisition system. The template can be created from scratch or derived from an existing one. Templates shared by other HRM users (including the administrator) can also be used. Choosing the correct parameters is absolutely crucial for obtaining high-quality deconvolution results.

    Use an existing parameter template (easy): When selecting an existing parameter template the contents are displayed in the panel on the right hand side. Make sure that the microscope type and the number of channels of the template match the images selected in Step 1/5.

    Create a new parameter template (elaborated): Click the New template button CreateTemplate22x22. Type a name for the new template and click ‘Create’. The template editor opens, select the correct number of channels and PSF type. Move on to the optical parameters and select the correct microscope type. For a detailed explanation on the remaining parameters please refer to section Deconvolution with the HRM.

  • RestorationParameters48x48 Step 3/5 - Restoration parameters: As in the previous step it’s possible to choose between an existing template or creating a new one.

    Use existing parameter template (easy): Select a parameter template and verify its contents on the preview shown on the right hand side panel. Particularly, pay attention to the value of the Signal to Noise ratio (SNR) (see Signal to Noise ratio for further help).

    Create a new parameter template (elaborated): Click the New template button CreateTemplate22x22. Type a name for the new template and click ‘Create’. Once in the template editor select a deconvolution algorithm (CMLE is a good choice) and an SNR. Follow the instructions of the SNR estimator as a guide for the SNR of the selected images. Set the background mode to automatic, the number of iterations to 40 and the quality change to 0.01. For more detailed fine-tuning follow the instructions at Deconvolution with the HRM.

  • AnalysisParameters48x48 Step 4/5 - Analysis parameters: This step is only active when 2 or more channels have been specified in the previous steps. When active, the Analysis step allows the user to execute Colocalization analysis on the deconvolved images.

    Use existing parameter template (easy): Select the analysis parameter template of your choice and verify that the values displayed on the preview on the right hand side panel match your analysis needs.

    Create a new parameter template (elaborated): Click the New template button CreateTemplate22x22. Type a name for the new template and click ‘Create’. Select whether colocalization should be enabled. For a colocalization run select the channels to be analyzed as well as the colocalization coefficients of interest. Set the threshold to “Automatic estimation” and the Colocalization map to “Pearson”. In order to further fine-tune the Colocalization parameters please refer to Deconvolution with the HRM.

  • LaunchJob48x48 Step 5/5 - Launch job: Select the output file format for the restored images. ICS and HDF5 are the recommended formats because they provide good dynamic range and the necessary meta data infrastructure to save all the image parameters. Plus, they allow for good compression levels that minimize the amount of disk space needed for storage. Next, review the parameter summaries as well as the image selection. If all the settings are correct then proceed to submit the job to the server by clicking SubmitJob30x22.

Queue#

After submitting the job HRM returns to the Home panel. Access the queue by clicking JobQueue22x22. A typical processing queue looks like the following:

JobQueueScreenshot

The queue is handled in an intelligent way, allowing jobs from different users to be processed at different times.

Results#

When a deconvolution and analysis job is finished a notification email is sent with a link to the result. Alternatively, go to the HRM home panel and click on the Results icon Results22x22. The contents of the Results folder will be listed. Select the image that you would like to visualize and a preview will be displayed on the right hand side panel:

ResultImages

For a detailed view of both the raw image and the restored image click on DetailedViewLink.

A results page opens showing MIP, SFP and slicer comparisons of the raw image versus the deconvolved image. Summary tables show information about possible scaling factors, colocalization results, image parameters and deconvolution parameters. Also, movies along the Z direction and/or through time will be available for download.

DetailedViewScreenshot

Tips & Tricks#

  • When a deconvolution run gives optimal results download the processed data from the detailed view by clicking on DownloadResults22x22.

  • Click ShareTemplate22x22 at steps 2, 3 or 4 to share any of the templates with one or more colleagues.

  • To optimize the deconvolution results it is necessary to understand the different properties of the image and some of the mechanisms behind deconvolution. This introductory chapter skipped details that can make a difference on images with spherical aberration, extreme SNR values, undersampling, etc. For a detailed explanation please see Deconvolution with the HRM.

Deconvolution with the HRM#

Home panel#

Once logged in HRM, the home panel is displayed:

HomePanel

From this page the user can manage deconvolution jobs as well as other HRM administrative tasks. The following shortcuts are available:

  • StartJob22x22 Launch jobs : Start new jobs for deconvolution, stabilization, chromatic aberration correction, colocalization, etc.

  • JobQueue22x22 Queue status : See all jobs. Manage owned jobs.

  • RawImages22x22 Raw images: Upload new data for deconvolution.

  • Results22x22 Results: View and download deconvolved data.

  • Statistics22x22 Statistics: Summary of job statistics.

  • Account22x22 Account: View and change login data.

Launch a job#

To start a new job with deconvolution, chromatic aberration, stabilization, or colocalization analysis click on Launch jobs StartJob22x22 in the home panel. This page describes the general workflow which is split into the following five main steps. The detailed description of all the parameters included by the templates used in this workflow is documented on the following sub-pages:

Image template#

An image parameter template consists of several microscopic pararameters relevant for deconvolution. To get a preview of the template contents select the template, the contents will be displayed on the right panel.

ParamPreviewScreenshot

Note

When editing a template help links HelpLink22x22 are displayed at key locations to point you to specific articles of the SVI-wiki.

Number of channels#

Number of fluorescent channels in the image.

NumberChannelsScreenshot

Note

Transmission channels can NOT be deconvolved with the algorithms currently available in HRM and should be skipped!

PSF Type#

To perform image deconvolution a Point Spread Function (PSF) is needed.

The Huygens software can compute a theoretical PSF from the image parameters used during deconvolution or it can use a measured PSF.

PSFTypeScreenshot

Depending on the user choice HRM will, at a later stage, ask for:

  • the path to the file containing the PSF if you selected Measured,

  • the settings to correct for spherical aberration if you selected Theoretical and there is a refractive index mismatch.

In most cases a theoretical PSF works fine.

Microscope type#

Choose among the supported microscope types: widefield, confocal, spinning disk, multiphoton, STED, STED 3D, SPIM, Rescan, and Array detector (Airyscan). Depending on the Huygens license some of these options might not show.

MicroscopeTypeScreenshot

Note

HRM requires the microscope type as input from the user. HRM will NOT load the microscope type from the selected images automatically.

Import metadata#

Some parameters are always present in the meta data of specific file formats and can be imported from the image at run time, while deconvolving the image, to save you time.

Note

When a parameter is missing from the meta data HRM needs input from the user. This is highlighted by a message like this: MetadataScreenshot3

Note

When a parameter is present in the meta data HRM can work without the input from the user. This is indicated with MetadataScreenshot2

At the end of the deconvolution job, HRM informs on the values of all used parameters as well as their origin (user input or meta data).

Numerical aperture#

The Numerical Aperture (NA) describes the amount of light coming from the focus that the objective can collect.

The NA depends on the half angle of the maximum cone of light that can enter or exit the lens. It is directly linked to the resolution of the objective.

NAScreenshot

Usually, the NA can be found engraved on the objective next to the magnification.

Note

Depending on the selected file format this parameter may be skipped, as explained in Import metadata.

Wavelengths#

Excitation and emission wavelengths of each channel. For the emission wavelength the central value of the emission spectrum of the fluorophore can be considered.

WavelengthsScreenshot

Note

Make sure to insert these values in the same order as they were acquired.

Objective Type#

Whether a dry (air) or immersion objective (water, glycerol, oil) was used. For other immersion types it is possible to enter their refractive indexes directly.

ObjectiveTypeScreenshot

Note

Several file formats report this value in the meta data. To leave empty please click on ResetChoice22x22.

Sample medium#

Whether glycerol, polyvinyl alcohol, vectashield or water was used to embed the sample.

For other embedding media it is also possible to specify their refractive indexes directly.

SampleMediumScreenshot

Note

Few file formats report this value in the meta data. To leave empty please click on ResetChoice22x22.

Voxel Size#

The voxel size or sampling size is a very important parameter in image deconvolution.

Note

According to the Nyquist criterion its value should not be larger than half the optical resolution of the imaging system.

HRM offers several utilities to help you set up this parameter correctly.

VoxelSizeScreenshot

Ideally, the optimal voxel sizes are calculated before acquiring the images. By doing so, one can ensure that the images are compliant with the Nyquist criterion. Click on NyquistCalculatorLink to determine how large the voxel sizes should be. By using these values, there will be no lost information during the image acquisition and the deconvolution will be able to restore the original signal better.

If the optimal voxel sizes have not been determined before the acquisition stage one can calculate the resulting sizes in widefield and spinning disk microscopy by using CCDCalculatorLink. Here the voxel sizes are calculated from the CCD camera element, the objective magnification, etc., although no optimal voxel size can be guaranteed.

Note

Make sure to set a voxel size consistent with the Nyquist criterion. Undersampled images will often show artifacts after deconvolution.

Lastly, for deconvolving time series set the time interval between subsequent frames.

TimeIntervalScreenshot

Among other things, this will help HRM to decide when to stabilize the image.

Using a measured PSF#

This option will only appear if ‘measured PSF’ was selected as PSF Type in a previous step.

Distilled PSFs need to be created beforehand using Huygens Professional and uploaded to the Raw images folder.

Note

One PSF image per channel. Multichannel PSFs are not supported.

When presented with the Distilled PSF file selection window,

DistilledPsfFileSelection1

browse for the distilled PSF appropriate for the channel(s) of the image.

DistilledPsfFileSelectionBrowse

Select the PSF file and click close. Repeat for all channels.

DistilledPsfFileSelection2

Afterwards, press save and return to the image parameter selection page.

Note

Files that can’t work as PSFs for the selected image(s) are crossed off and displayed in red.

Pinhole Radius#

Pinholes are used in confocal, spinning disk, STED, STED 3D and Rescan microscopy to get rid of out-of-focus light. Since there’s no pinhole in widefield, two photon and SPIM microscopes HRM skips this parameter in those cases.

PinholeRadiusScreenshot

Note

HRM needs the value of the pinhole backprojected on the specimen.

Further help on how to calculate the backprojected pinhole radius can be found on PinholeCalculatorLink.

Pinhole Spacing#

Spinning disk microscopy uses more than one pinhole to speed up image acquisition. The backprojected distance between these pinholes also plays a role in image deconvolution. HRM skips this parameter for all other microscope types.

PinholeSpacingScreenshot

Click on PinholeCalculatorLink for further help on the calculation of the backprojected value.

STED parameters#

If the selected microscope type is STED or STED 3D then a few STED parameters need to be specified to describe the STED acquisition. When working with other microscope types HRM will skip these parameters.

First, select the STED depletion mode: Pulsed, Continous wave gated detection, Continous wave non gated detection or Off/Confocal.

STEDModeScreenshot

Note

STED and confocal microscopy are often combined. That’s why even if the selected microscope type is STED it’s still possible to set specific channels as confocal at this point.

Set the STED saturation factor of each channel. Typical values are in the range of 10 to 50. The higher this factor, the more suppression of fluorescence away from the optical axis, the more resolution.

STEDSaturationScreenshot

Next, set the STED depletion wavelength of each channel. Notice that Channel 1 is grayed out in these figures because it was set as confocal.

STEDWavelengthScreenshot

The STED immunity fraction tells Huygens the percentage of fluorescent molecules that are not susceptible to the STED laser. Typical values are in the range 0% to 10%.

STEDImmunityScreenshot

Finally, depending on whether the microscope type is STED 3D or not, set the percentage of STED 3D per channel. This tells Huygens how much power was used in the Z depletion beam. The remaining power is used for the vortex path.

STED3DScreenshot

SPIM parameters#

If the selected microscope type is SPIM then a few SPIM parameters need to be specified to describe the SPIM acquisition. When working with other microscope types HRM will skip these parameters.

First, select the SPIM excitation mode of each channel: Gaussian light sheet, Gaussian MultiView light sheet, High fill factor (cylinder), or High fill factor (scanning beam).

SPIMExcModeScreenshot

Set the width of the Gaussian light sheet for the channels acquired with one of the Gaussian modes. The field will be grayed out for the other channels.

The width is defined as the distance between the two (symmetric) points of the Gaussian profile where the intensity values drop to 2/e^2 of the peak value.

SPIMGaussWidthScreenshot

Set the SPIM Focus Offset of the light sheet. This is the distance along the optical axis of the detection lens between the focus of the illumination lens and the focus of the detection lens.

SPIMFocusScreenshot

Similarly, set the SPIM Center Offset of the light sheet. This is the distance along the optical axis of the illumination lens between the focus of the illumination lens and the focus of the detection lens.

SPIMCenterScreenshot

Set the SPIM NA for the channels aquired with the one of the High Fill Factor modes. This is the Numerical Aperture of the illumination lens.

SPIMNAScreenshot

Then, the fill factor of the illumination lens, for the channels acquired with one of the High Fill Factor modes. This is the ratio between the beam width and the diameter of the objective pupil in the illumination lens.

SPIMFillScreenshot

Lastly, the SPIM Illumination Direction. This can be left, right, bottom, top for any of the non-MuVi (Multi-View) excitation modes; and right+left or top+bottom for the Gaussian MuVi excitation mode.

SPIMDirectionScreenshot

Spherical Aberration correction#

Spherical aberration is mainly caused by a mismatch between the refractive indexes of the objective immersion medium and the sample embedding medium.

HRM will automatically detect this mismatch and ask whether the aberration should be corrected for when using a theoretical PSF.

Note

Spherical aberration can be corrected for by creating different theoretical PSFs (with slightly changing shapes) at different depths: depth-dependent PSF.

DepthDependentPSFScreenshot

When using a depth-dependent PSF one also needs to specify whether the first plane in the dataset is closest or farthest to/from the coverslip.

DataOrientationScreenshot

The Correction mode allows for a more detailed choice as to how the depth-dependent PSF should vary with depth.

SACorrectionModeScreenshot

  • Automatic correction: will generate a depth-dependent PSF where the PSF is automatically selected at each depth, as explained above.

  • Advanced correction: allows to specify further details about the depth-dependent PSF.

The Advanced correction will further enable a number of advanced options.

SAAdvancedScreenshot

  • Depth-dependent PSF on few bricks: a different PSF will be generated for each Z brick in which the original data is split.

  • Depth-dependent PSF slice by slice: a different PSF will be generated for each slice.

  • Depth-dependent PSF on few slabs: several PSFs will be generated for each Z brick. This option is memory-consuming but the best choice when the spherical aberration is very strong.

Note

Splitting the original data into bricks while deconvolving not only helps to correct for spherical aberration but it also minimizes the amount of RAM memory needed for deconvolution.

Restoration template#

A restoration parameter template consists of a number of options which provide Huygens Core with information on the restoration procedure. To get a preview of the template contents select the template, the contents will be displayed on the right panel.

Note

When editing a template help links HelpLink22x22 are displayed at key locations to point you to specific articles of the SVI-wiki.

Deconvolution algorithm#

From HRM 3.7 onwards it is possible to select one deconvolution algorithm per image channel. In most cases this will not be necessary and the user will likely find it convenient to deconvolve all the image channels with the same deconvolution algorithm.

For each channel choose one of the deconvolution algorithms from the corresponding drop down widget.

DeconAlgsScreenshot

The available choices are:

  • Classic Maximum Likelihood Estimation (CMLE): CMLE is the method of choice under most circumstances. In case of doubt, CMLE should be used.

  • Quick Maximum Likelihood Estimation (QMLE): QMLE is faster than CMLE, but gives slightly less precise solutions in some cases. One may consider using QMLE in compute-intensive situations, for example, when deconvolving widefield 3D-time series.

  • Good’s roughness Maximum Likelihood Estimation (GMLE): GMLE is a good alternative for high-noise images, such as STED or confocal.

  • Skip : for not deconvolving this channel and keeping the raw data instead.

Note

Skip all channels of an image to use HRM as a pure batch file converter, chromatic aberration corrector, time stabilizer, colocalization analyzer, etc.

Signal to Noise ratio#

In the Huygens Software the Signal-to-Noise ratio (SNR) is treated as a regularization parameter, i.e., a means to control the sharpness of the deconvolution result.

Yet, please be aware of the effect of extreme SNR values on image deconvolution: too high SNR values can produce restoration artifacts; too low SNR values can lead to smooth structures.

Note

After a little practice it is possible to assess the SNR range for deconvolution visually. In general, the SNR should increase with the quality and amount of signal of the raw data.

There are different acquisition settings that have an impact on the quality of the recorded signal. Changing these in the acquisition system will most likely require a modification of the SNR value for deconvolution. These acquisition settings are:

  • Gain / offset

  • Time exposure / scanning velocity

  • Summing / averaging

  • Laser power

  • Spectral detection range

Because these settings are typically different for each channel HRM will require an SNR value per channel, like this:

SNRScreenshot

As a guide, these are typical SNR values for different microscopy tecniques:

  • Confocal: between 20 and 40.

  • STED: between 10 and 20.

  • Widefield: between 40 and 60.

HRM offers an automatic SNR estimator to determine suitable SNR values for the raw images. Click on SNREstimatorLink to use the SNR estimator.

In a new page you will be asked to select an SNR estimation method.

SNRAlgorithmScreenshot

The Auto method gets good estimations on images without a baseline. When working with images that contain a baseline the Legacy method can be used instead.

Next, select an image representative of the batch selected in Select images (1/5). Press Calculator22x22 for the SNR estimation:

SNREstimationScreenshot

The output of the SNR estimator shows a region of the original data next to 4 different noise simulations of the same region. In bold letters the SNR of the simulation that most resembles the original image.

By pressing Next22x22 the estimated SNR values are copied into the restoration parameter template.

Acuity#

As of HRM 3.8 the acuity parameter controls the sharpness of the result.

In older Huygens and HRM versions this could be controlled by setting lower or higher than expected Signal to Noise ratio values for the image.

If you would like to keep working like in the older versions simply set the acuity mode to legacy:

Acuity1

For integrating the acuity parameter in your workflows and to leave the legacy mode behind enable the acuity mode and set acuity values for each channel. The accepted values range between -100 and +100.

Acuity2

  • Positive acuity: the more positive the acuity, the sharper the result and the less noise suppression (or potentially noise amplification).

  • Negative acuity: the more negative the acuity, the more noise suppression and the less sharpness.

Crop image#

HRM can intelligently crop your images without losing important data.

CropScreenshot

Select from:

  • Apply conservative crop: to save computation time.

  • Do not crop the image: if computation time is not an issue.

Note

The time needed to deconvolve an image increases more than proportionally with the image volume. Thus, cropping the image will speed up its restoration and the processing of the HRM queue.

Bleaching Correction#

Huygens can automatically estimate the amount of bleaching in the image and correct for it. This type of correction is mostly necessary for 2 types of images:

  • Images from widefield-like systems. Since the specimen is exposed to large amounts of light it can be easily bleached.

  • Time series from any type of microscope. Depending on how long the time series is the specimen can also be exposed to large amounts of excitation light.

Note

2D/3D images froms confocal-like systems (no time series) don’t need to be corrected for bleaching.

When presented with the Bleaching correction option, it is recommended to select

BleachingCorrection1

for any time series and/or widefield-like images.

Select

BleachingCorrection2

for all of the other images.

Stabilization in Z#

This option will only be shown when restoring STED images (including STED 3D). Due to the high lateral resolution in STED, image acquisition in more sensitive to drift in STED than in other microscopy modes.

ZStabilizationScreenshot

Note

It is strongly recommended to select Z stabilization on STED images.

The stabilization is performed before deconvolution. This significantly improves the restoration results.

Z stabilization is also recommended on STED 3D images although Huygens can automatically skip it depending on the PSF shape of each particular case.

Array Detector Reduction Mode#

This option will only be shown when restoring Array Detector images (Airyscan, SPAD, etc). Array Detector images contain one acquisition per detector. The user can tell Huygens how to combine the data from all the detectors for deconvolution.

ReductionModeScreenshot

The following options are possible:

  • All: the images from all detectors are centered and combined, thus increasing the SNR. The resulting, combined image is then deconvolved.

  • No: the independent detectors are not combined prior to deconvolution. They are used as separate inputs of a ‘parallel’ deconvolution.

  • Core all: Same as All but taking into account the central detectors only.

  • Core no: Same as No but taking into account the central detectors only.

  • SuperY: Create an image with 4 times as many samples in Y. This is mostly useful when dealing with images recorded with the Zeiss Airyscan in fast mode.

  • SuperXY: Create an image with double the samples in X and Y. Thus, producing an image with 4 times more samples. This is a good option when dealing with images that have been acquired well under the Nyquist sampling rate.

  • Auto: Automatic selection of one of the above mentioned modes depending on the microscopic parameters and detector model of the image.

In all cases the SNR value specified in Signal to Noise ratio is for the central detector. Huygens will scale the SNR for the combined detectors automatically.

Background mode#

The background intensity is a nearly constant value that is present everywhere in the image.

BackgroundScreenshot

Three options are available for background correction. These options can return slightly different values, therefore this choice can affect the deconvolution result:

  • Automatic background estimation: This estimation usually works well. The background is estimated within a region with a low mean value.

  • In/near object: The background is estimated around intensity peaks. This option can be interesting, for example, when having bright little objects in a cell with a strong cytoplasmic background.

  • Remove constant absolute value: To make sure that the same background level is removed from all the images in the batch, insert manually a measured mean background for each channel. This option is typically useful for those interested in doing fluorescence quantification or stitching.

Stopping criteria#

The restoration algorithms offered in HRM, CMLE, QMLE, and GMLE, are iterative methods. This means that the algorithms compute sequential solutions which converge to a stable result.

Deconvolution will stop when either of the following two conditions is met.

StopCriteriaScreenshot

  • Number of iterations: sets the maximum number of iterations that Huygens will compute.

  • Quality change: how much the results of two consecutive iterations differ. If two subsequent results differ less than this factor then convergence has been reached.

StopCritPerChanScreenshot

As of HRM 3.9 it is possible to set the stopping criteria seperately for each channel. Leaving later channels empty will use the last set value.

Chromatic Aberration Correction#

This option will only be shown when restoring multi channel images. In order to let HRM know that an image batch contains multi channel images please set the number of channels correctly, as explained in Number of channels.

The restoration template editor contains a section for post-deconvolution operations. Options for these operations (chromatic aberration correction and stabilization of time series) only show up when applicable, i.e, multichannel images and time series.

Therefore, the following section will only be displayed when restoring multi channel images:

ChromaticScreenshot

Choose a reference channel:

ChromaticScreenshot2

The chromatic aberration can be described by an x-y-z shift + rotation + scale (zoom) of each channel with respect to the reference channel. Therefore, by definition the reference channel has no x-y-z shift, rotation or scale. For the other channels, type in the shifts, rotations and scales.

ChromaticScreenshot3

The table will contain one entry per channel.

For an accurate estimation of the chromatic aberration one can use a local installation of Huygens Professional or Huygens Essential, see Chromatic Aberration Corrector.

Use the estimated x-y-z shifts, rotations and scale values reported by Huygens Professional or Essential to fill out the table. All images recorded with the same settings and the same microscope can be corrected with the same chromatic aberration values.

As of Huygens 21.10.1 the Chromatic Aberration correction has an option for higher order corrections (e.g.: barrel and pincushion distortions). The description of these deformations can be imported into HRM from the corresponding Huygens template. However, due to the complexity of the parameters they can’t be either edited or viewed in HRM.

HRM 3.8 and higher will let you choose between the higher-order correction and the 5 parameter correction (x,y,z, rotation, scale) when importing templates from Huygens. Please do keep in mind that the extra parameters will be handled under the hood and are not displayed in the HRM UI.

An option to edit the shifts, rotation and scale while discarding the higher-order corrections from a Huygens template will appear on importing, as follows:

ChromaticScreenshot4

Note

For skipping the chromatic aberration correction simply leave the table fields empty.

Stabilization of time series#

This option will only be shown when restoring time series. In order to let HRM know that an image batch contains time series please set the time interval correctly, as explained in Voxel Size.

The restoration template editor contains a section for post-deconvolution operations. Options for these operations (chromatic aberration correction and stabilization of time series) only show up when applicable, i.e, multichannel images and time series.

Therefore, the following option will only be displayed when restoring a time series:

TStabilizationScreenshot

Set a stabilization method:

TStabilizationScreenshot2

  • Center of mass: works best if the image contains a single large object. No objects should cross the image borders.

  • Correlation: for general x-y-z translations and axial rotations. Adjacent time frames will be compared. The software will try to find the best alignment by maximizing structural overlap.

  • Model based: if the geometry of the imaged object did not change much during the acquisition.

Choose whether to detect and correct rotations:

TStabilizationScreenshot3

Lastly, specify the cropping mode for the resulting, stabilized time series:

TStabilizationScreenshot3

  • Original: to crop the result to the size of the raw data.

  • Full: to preserve the size of the stabilized data.

  • Tight: to crop away large background regions.

Note

Depending on the cropping mode the dimensions of the result and the raw data will differ. This will become noticeable when comparing the data later. See Results - detailed view.

Hot Pixel Correction#

Hot Pixel Correction masks need to be created beforehand using Huygens Professional or Essential and uploaded to the Raw images folder.

Note

Multichannel masks are supported.

When presented with the Hot Pixel Correction file selection window,

HotPixelCorrection1

browse for the mask of the camera used for the image acquisition.

HotPixelCorrection2

Select the Hot Pixel mask and click close.

Afterwards, press save and return to the image parameter selection page.

HotPixelCorrection3

The correction will only be applied to those images of the batch that have the same XY dimensions as the mask.

Note

This correction is optional. The selection can be left empty. Use the reset button to unselect a previously selected mask.

Analysis Template#

An analysis parameter template consists of a number of options that provide Huygens Core with information about the type of analysis to execute on the images. To get a preview of the template contents select the template, the contents will be displayed on the right panel.

Note

When editing a template help links HelpLink22x22 are displayed at key locations to point you to specific articles of the SVI-wiki.

Colocalization#

Colocalization is a type of analysis which measures the amount of overlap between the objects of two channels.

ColocalizationScreenshot

Here simply select whether or not colocalization analysis should be performed after deconvolution.

Note

Colocalization can only be performed on multichannel images.

Channels#

Select the channels to be analyzed.

ColocChannelsScreenshot

All the combinations of the selected channels will be studied. For example, the selection shown in the figure above will result in the analysis of the following channels:

  • 0 and 1,

  • 0 and 2,

  • 1 and 2.

Colocalization coefficients#

HRM can report all the colocalization coefficients that are most widely used in fluorescence microscopy.

Select here the colocalization coefficients for the analysis:

ColocCoefficientsScreenshot

A colocalization report with all these findings will be ready when the job is finished.

For further information on specific colocalization coefficients please read this article from the SVI wiki.

Threshold#

In order to discard background signals from the colocalization analysis it is possible to set a threshold level.

ColocThresholdScreenshot

The automatic option typically works well for most purposes. Yet, it’s possible to specify a threshold per channel to discard particular features of each colour.

Colocalization map#

While a colocalization coefficient quantifies the level of overlap between two whole channels, a colocalization map displays the value of a specific colocalization coefficient for each voxel of the two channels.

ColocMapsScreenshot

Therefore, a colocalization map is a 3D image of the level of overlap between the two channels, according to a specific coefficient.

It is possible to choose between the 4 most widely used colocalization maps. The maps will be displayed in the colocalization report after the job is finished.

Note

The colocalization maps help us to assess the colocalization regions visually.

As an example the below figure shows the deconvolution result of channels 0 and 3 next to the colocalization map (Pearson coefficient) of the same channels.

ColocMapsScreenshot2

Select images (1/5)#

In step 1 - SelectImages22x22 Select Images - the user can add images for deconvolution. A batch of images with the same properties can be selected with Ctrl+click or Shift+click and added in one go.

SelectImagesScreenshot

Select the file format from the drop down widget and use DownArrow22x22 UpArrow22x22 to add images to the Selected images area.

Note

The images of a batch must share the same microscopic parameters in order to obtain good deconvolution results because they will be restored with the same settings. This is generally true if the images are recorded with the same setup.

When an image is selected a preview is displayed on the right panel whenever possible. If not yet available, a button shows up GeneratePreviewLink to generate the preview on the fly.

Note

Image previews also display the image dimensions, number of channels, and sampling sizes in the overlay.

By default no particular image format is preselected and HRM shows all images available in the user’s raw images folder. Select a file format to filter out images from other file extensions.

The Image Parameters (2/5)#

In step 2 - ImageParameters22x22 Image Parameter - the microscope settings can be specified and saved. The image parameters are grouped in templates. A parameter template can be reused in future deconvolution jobs. This will be useful when there are more images recorded under the same conditions. Moreover, the parameter templates can be shared with one or more HRM users.

The following selections are possible at this stage:

  • Admin image templates: parameter templates created by the HRM administrator to be used as references. These templates cannot be changed directly. Instead, they can be copied to Your image templates (see below) for further changes. For copying to Your image templates select the admin template and use DownArrow22x22.

AdminTemplatesScreenshot

  • Your image templates: the image templates that the user can use directly. All templates in this area may be selected, edited, removed, etc.

UserTemplatesScreenshot

New templates can be added to the list by creating them from scratch using the CreateTemplate22x22 button, by using the image metadata FromImage22x22, by importing a shared template ShareTemplate22x22, or by modifying an existing template CloneTemplate22x22. To modify a template simply click on the EditTemplate22x22 button.

Note

CreateTemplate22x22 EditTemplate22x22 CloneTemplate22x22 FromImage22x22 HuygensTemplate22x27 ShareTemplate22x22 FavouriteTemplate22x22 DeleteTemplate22x22 show tooltips describing their actions w.r.t templates. Namely, create, edit, clone, import from an image, import from a Huygens template, share, mark as favourite and delete.

The Restoration Parameters (3/5)#

In step 3 - RestorationParameters22x22 Restoration Parameter - the restoration settings can be specified and saved. As in the previous secion the restoration parameters are grouped in templates. A template can be reused in future deconvolution jobs. This will be useful when other images need to be restored with the same settings. Moreover, the templates can be shared among HRM users, fostering collaboration and re-usage of good restoration settings.

The following selections are possible at this stage:

  • Admin restoration templates: parameter templates created by the HRM administrator to be used as references. They can be copied and edited by the HRM users. In order to use them, they first need to be copied to Your restoration templates by using DownArrow22x22.

  • Your restoration templates: the restoration templates that the user can use directly. All templates in this area may be selected, edited, removed, etc.

Note

CreateTemplate22x22 EditTemplate22x22 CloneTemplate22x22 HuygensTemplate22x27 ShareTemplate22x22 FavouriteTemplate22x22 DeleteTemplate22x22 show tooltips describing their actions w.r.t templates. Namely, create, edit, clone, import from a Huygens template, share, mark as favourite and delete.

Analysis parameters (4/5)#

In step 4 - AnalysisParameters22x22 Analysis Parameters - the analysis settings for your images can be specified and saved. As always, the analysis parameters are grouped in templates. A parameter template can be reused in future deconvolution and analysis jobs. This will be useful when the same type of analysis has to be performed on other images. Moreover, the parameter templates can be shared among HRM users, fostering collaboration and re-usage of good analysis settings.

The following selections are possible at this stage:

  • Admin analysis templates: parameter templates created by the HRM administrator to be used as references. They can be copied and edited by the HRM users. In order to use them, they first need to be copied to Your analysis templates by using DownArrow22x22.

  • Your analysis templates: the analysis templates that the user can use directly. All templates in this area may be selected, edited, removed, etc.

Note

CreateTemplate22x22 EditTemplate22x22 CloneTemplate22x22 ShareTemplate22x22 FavouriteTemplate22x22 DeleteTemplate22x22 show tooltips stating their action w.r.t templates. Namely, create, edit, clone, share, mark as favourite and delete.

Launch the job (5/5)#

In this last step several summaries display all the chosen parameters.

Also, the output format for the result images can be selected at the top of the page:

OutputFormatScreenshot

  • ICS, ICS2 and HDF5: support multi-channel images, 32 bit dynamic range (preserve all image details) and all the microscopic metadata parameters. Furthermore, they support high compression levels. Since deconvolved images often contain background regions with near 0 intensities the compression algorithms usualy manage to greatly reduce the size of the images. For all these reasons these are the formats recommended for further work with Huygens.

  • TIFF: this format can be used for analysis such as counting or segmentation. For quantification one needs to scale the TIFF image back to its original dynamic range. The corresponding scaling factors are reported by HRM and can be found in Parameter summaries.

  • IMS, OME-XML, R3D: formats offered for compatibility with other programs.

Next, review all the selected parameters before submitting the job to the server. It’s possible to go back to the image, restoration, and analysis template editors by clicking on the corresponding links.

Click on ImageParametersLink to change the image parameters.

SummaryParamsScreenshot

Click on RestorationParametersLink to change the restoration parameters.

SummaryParamsScreenshot2

Click on AnalysisParametersLink to change the analysis parameters.

SummaryParamsScreenshot3

To change the image selection click on SelectedImagesLink.

SelectedImagesScreenshot

Finally submit the job by pressing SubmitJob30x22.

Queue status#

After submitting a job HRM returns to the home panel. The Queue Status button shows how many queued jobs you own, as follows:

QueueStatusScreenshot

Click on the button to get a detailed view of the job queue.

QueuedJobsScreenshot

HRM manages the deconvolution of multiple jobs owned by different users through a smart queue. The job being processed is marked in green.

The server field will show the name of the machine and, when applicable, the number of the GPU card processing the image. HRM can process multiple jobs at the same time.

Note

The total number of processing machines and GPU cards defines the jobs than HRM can process in parallel.

To delete any of your jobs, select them in the queue table and click TrashBin22x22.

Note

Depending on the HRM configuration settings, a notification email will be sent to the job owner when the job is finished.

If the job’s result seems wrong, try to verify if there is a mistake in the settings. Contact the HRM administrator otherwise.

Results - detailed view#

When the job finishes, the files are placed in the Results22x22 Results folder, accessible via the home panel.

Click on an image result for further inspection as explained in Results .

The detailed view shows the following information:

  • MIP of original vs deconvolved,

  • SFP of original vs deconvolved,

  • Z Slicer of original vs deconvolved,

  • T Slicer of original vs deconvolved,

  • Stack movie of deconvolved,

  • T movie of deconvolved,

  • T SFP movie of deconvolved,

  • Colocalization results,

  • Parameter summaries,

  • Huygens log.

Note

The number of tools shown in the detailed view depends on the type of restoration, the image geometry and the HRM configuration.

Comparing MIPs#

A comparison of the Maximum Intensity Projections of the raw image and the restored image shows the effect of deconvolution. This can be assessed in both XY and XZ projections.

MIPResultScreenshot

Comparing SFPs#

A comparison of the Simulated Fluoresence Process in both the raw image and the restored image also shows the effect of deconvolution and difference in noise.

SFPResultScreenshot

Comparing Z Slices#

The slicer allows for a comparision of the raw image and the restored image slice by slice along the Z direction at any depth.

ZSlicerResultScreenshot

Comparing T frames#

The time slicer allows for a comparision of the raw image and the restored image frame by frame.

TSlicerResultScreenshot

Z, T and T-SFP movies#

Click on the corresponding links to download any of the movies to your local computer.

MoviesLinks

Note

These automatically made movies are quite useful for prepraring presentations.

Colocalization#

The selected colocalization coefficients of each two channels are listed in a table with an entry per frame.

ColocTableScreenshot

Also, 2D histograms show the correlations between any two channels.

2DHistogramScreenshot

Lastly, the colocalization maps show the regions where colocalization between any two channels is strongest.

ColocMapsScreenshot2

Parameter summaries#

HRM also gives feedback on all the parameter values used during deconvolution. This is particularly useful when the parameters are read from the image metadata.

ParameterSummaryScreenshot

Notice that green entries indicate parameters loaded from the image metadata, whereas violet entries indicate parameters defined by the user.

If the image had to be scaled to fit in the output file format (some formats have very limited dynamic ranges) HRM will show the scaling factors for further quantification:

ScalingFactorsScreenshot

Huygens log#

The exact steps followed by Huygens to process the data can be found on the Huygens log, under the link HuygensLogLink .

Note

All these results can be donwloaded along with the deconvolved dataset by clicking DownloadResults22x22 at the top of the page.

Tips & Tricks#

  • File uploads: When using the browser uploader it is possible to upload compressed files containing more images. HRM will uncompress the file and set the contents in your raw folder.

  • File uploads: Add more files to your selection by clicking AddOtherFileLink. Use drag&drop from your desktop into the browser.

  • Image previews: Select an image and click on Generate preview to visualize the image contents plus the dimensions and sampling sizes. The colours used in the preview depict the wavelengths provided by the image metadata.

  • Voxel sizes: Whenever possible HRM highlights in yellow the ideal voxel sizes according to the Nyquist criterion.

  • SNR estimation: Notice that it’s possible to zoom in the thumbnails displayed by the SNR estimator by moving the mouse pointer over the thumbnails. This can be useful to confirm the correctness of the SNR

  • SNR estimation: The SNR can highly influence the deconvolution result. On the one hand, if the deconvolution result looks too smooth and details are missing, a higher SNR value can be used. On the other hand, if the result looks too grainy a lower SNR value may be better.

  • Colocalization: Filter out unsignificant colocalization coefficients by using the Highlight button of the colocalization section in the detailed view.

  • Select images (1/5): Tick the “When applicable, load file series automatically” checkbox if several independent files should be loaded into a single image.

For instructions on how to get an HRM account, got to this section.

Additional features#

OMERO connector#

HRM can import and export images from/to a local or remote OMERO server.

Note

This feature is not active by default. Ask the HRM administrator for more information about the HRM/OMERO connector.

If the connection between HRM and OMERO is enabled the OMERO logo Omero22x22 will be is displayed in the Raw images RawImages22x22 and Results Results22x22 folders.

Click on Omero22x22 . The following window will ask you to enter your OMERO login credentials.

OmeroCredentialsScreenshot

Upon logging in successfully a file tree will be displayed listing all the images in the OMERO repository that you are allowed to visualize, like this:

OmeroTreeScreenshot

Note

The OMERO credentials and file tree will be used throughout the HRM session. When the session is closed HRM will remove the OMERO credentials from the cache.

The OMERO tree is requested automatically only the first time in every HRM session. This saves waiting time in subsequent import/export operations with OMERO. To force a tree rebuild click Refresh22x22 .

The following actions are possible:

  • Import data from OMERO: In the Raw images RawImages22x22 folder select an image from the OMERO tree and click UpArrow22x22. The image will be imported to HRM with extension .ome.tiff. Select more images with Ctrl + click for importing multiple images in one go.

  • Export data to OMERO: In the Results Results22x22 folder select the HRM image to be exported. Select the target OMERO dataset. Click DownArrow22x22 . The image will be attached to the OMERO project with an annotation describing all the parameters used for deconvolution. Select more images from the Results folder for exporting multiple images in one go.

Usage Statistics#

The user statistics can be reached from the HRM home panel.

Click on Statistics Statistics22x22 to create reports about the deconvolution and analysis jobs within a specific time window.

The following reports are possible:

  • Input file format.

  • Output file format.

  • Type of PSF used during deconvolution.

  • Microscope type.

  • Run time per user.

StatisticsScreenshot

User account#

Click on Account22x22 in the home panel to change any of the details linked to your HRM account.

AccountScreenshot

Administration of the HRM#

HRM consists of two main components: a web based interface and a queue manager.

The web interface allows:

  • the management of users by the system administrator;

  • the management of parameter sets (templates) that all users can copy or use directly;

  • the creation of deconvolution jobs, including image selection, setting microscopic, restoration and analysis parameters;

  • inspecting the job queue status, and allowing the users to delete their own jobs from it;

  • previewing and analyzing deconvolved images, including a slicer, MIP and SFP renderers, movies and colocalization results;

  • sharing templates among users;

  • visualizing user and jobs statistics.

HRM is equipped with a simple http file uploader/downloader to send raw images from the user’s local machine to the HRM server, as well as to retrieve the deconvolution results from the server. The server administrator can set up a limit for these transactions.

The queue manager, running the background, dispatches:

  • the jobs created via the web interface to any of the dedicated servers running Huygens Core.

  • the emails to inform the users that the job is finished and that the restored datasets are available.

Installation and requirements#

To install HRM the following pre-requisites (at least) must be fulfilled:

  • Operating system: Any recent Linux distribution. Based on Debian or RHEL.

  • Huygens Core: HRM is just an interface and needs Huygens Core to perform deconvolution on the raw images. Note that Huygens Core needs a license.

  • Apache2 web server.

  • PHP version5.6: Both the HRM queue manager and the web interface are written in PHP and need PHP to operate.

  • MySQL or PostgreSQL: A relational database management system is required to store deconvolution parameters, job descriptions and, optionally, user accounts.

  • A file server: To temporarily store input and restored datasets.

The setup is highly configurable, since the file server, the processing servers and the queue manager can either be all hosted by the same machine or be distributed across two, three or more computers.

To follow the steps for a guided installation please see the installation page at the HRM project’s site.

Administrator’s options#

Log in to HRM with the credentials of the administrator. Instead of the regular user home panel HRM will display the administrator home panel, like this:

AdminHomePanelScreenshot

There are a number of extra options that are available to the administrator only:

  • Manage users: Add, remove, edit, enable and disable users. Alternatively, HRM allows for LDAP/Active Directory user management.

  • Queue status: Manage jobs from all users.

  • Global statistics: See statistics from all users and jobs, including microscope types, PSFs, research groups, dates, etc.

  • Database update: Carry out a database update when a new HRM release requires it.

  • System summary: Get an overview of all the versions and configuration options that play a role in HRM.

  • Check for updates: Get automatic feedback on whether you are running the latest HRM version.

  • Create global templates: The administrator can create global templates accessible to all users. This is meaningful for lowering the threshold for those beginning users who need assistance to start deconvolving their raw data. Global templates can be created at any of the states where templates are required: The Image Parameters (2/5), The Restoration Parameters (3/5) and The Restoration Parameters (3/5).

  • Servers & GPUs: Add and remove processing machines and GPU cards. This has an effect on the total number of jobs that can run in parallel.

  • HuCore licenses: Get an overview of the installed Huygens license.

Version upgrade#

Note

Before upgrading HRM please proceed to backup the HRM database, images and source files.

To upgrade to a new version, download the latest version from here. Then follow the intructions on specific version upgrades.

Database update#

Note

The HRM database should NOT be deleted and replaced by a newer version.

The HRM database contains the existing users, statistics, parameter templates, etc. To update these contents to the latest release click on Database Update UpdateDB22x22 from the admin home panel and follow the instructions.

In order for this update to work properly it is advised to upgrade the HRM source code before upgrading the database.

System configuration#

HRM can be configured during the installation. The configuration settings are saved in a configuration file. Some settings, as the maximum upload limit, need to be adjusted both in HRM and in PHP.

For example, if the PHP configuration file states a max upload file size of 256MB, this is applicable to all programs using PHP. Suppose the HRM settings state that the max upload limit is 200MB, since 200MB is lower than 256MB, the HRM configuration does not conflict with the PHP configuration and 200MB is the maximum allowed file size.

Note

The PHP configuration file: /path/to/php/php.ini

The HRM configuration file: /path/to/hrm/config/hrm_config.inc

How HRM communicates with Huygens Core#

For each deconvolution task in the job queue the HRM queue manager automatically generates a Huygens Batch template for Huygens Core that

  • loads the raw image from a source directory,

  • applies the microscopic parameters to it as defined by the user or reads the microscopic parameters from the image metadata,

  • optionally loads another image containing the microscope Point Spread Function,

  • deconvolves the image using the restoration parameters chosen by the user,

  • optionally applies a chromatic aberration correction,

  • optionally stabilizes the time series,

  • optionally computes the colocalization coefficients of multi-channel images and generates colocalization maps,

  • stores the resulting restored image in a destination directory,

  • generates several visualizations of the raw and deconvolved images for the user to see the effect of the restoration,

  • and finally writes a tag in the destination directory to inform the HRM queue manager that the job is finished.

When the job is finished the queue manager optionally sends the user an e-mail announcing the end of the job and its status. The administrator may configure this.

Multiple jobs can be processed in parallel depending on how HRM is configured, the multiprocessing capabilities of the server, the number of available computation servers and GPU cards.

Tips & Tricks#

  • Use the global statistics to get an idea on which microscopes are used most, which file formats, PSFs, etc.

  • On the home panel, click on System summary SystemSummary22x22 to get an overview of your current HRM settings. Expand this information with the PHP settings and/or test the HRM e-mails by clicking on LightBulb18x22.

  • When performing an HRM upgrade disable all users first. Upon successfully upgrading HRM enable the users back again.

  • If you experience unexpected behaviour from the HRM queue manager, such as a deleted job which persists in the queue, restart the HRM daemon.

  • Encourage your users to save deconvolved data in ICS or HDF5 formats since the dynamic range and metadata parameters are conserved (unlike in TIFF). Moreover both ICS and HDF5 allow for good compression rates.

Clean a Stalled Queue in HRM#

It could happen that the queue breaks or freezes and the database is polluted with outdated information.

To fix this, one must currently go and clean up a few places in the hrm database as well as restart the queue manager. Here is a short checklist of what to do.

  1. shut down the hrm daemon by using

sudo /etc/init.d/hrmd stop

or

sudo systemctl stop hrmd
  1. go to the hrm database and do the following

    1. Remove broken or killed jobs from the job_* tables

    2. Make sure that the server table has a status of ‘free’ and job set to NULL

    Both measures can be achieved with the following SQL script:

DELETE FROM job_analysis_parameter WHERE setting IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_analysis_setting WHERE name IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_files WHERE job IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_parameter WHERE setting IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_parameter_setting WHERE name IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_task_parameter WHERE setting IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_task_setting WHERE name IN (SELECT id FROM job_queue WHERE status="broken" OR status="kill");
DELETE FROM job_queue  WHERE status="broken" OR status="kill";
UPDATE server SET status= 'free', job = NULL;
  1. restart the hrm daemon

sudo /etc/init.d/hrmd start