Commit 3c30bf9f authored by gonciarz's avatar gonciarz

First increment of documentation

parent 67776825
# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
SOURCEDIR = source
BUILDDIR = build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=source
set BUILDDIR=build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd
================
Changelog
================
* 1.0.19
- Discrete region sampling (DRS) is finally available in official release
* 1.0.18
- not supported anymore package ``javaml`` is not used in MosaicSuite anymore
* 1.0.17
- Results table in Region Competition is shown only in GUI or Macro mode (hidden in batch mode)
- Not mavenized external jars are now embedded in MosaicSuite repository
.. important::
For information about previous developments not listed here please refere to `old MosaicSuite site <http://mosaic.mpi-cbg.de/?q=downloads/imageJ>`_.
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
# import os
# import sys
# sys.path.insert(0, os.path.abspath('.'))
# -- Project information -----------------------------------------------------
project = 'MosaicSuite'
copyright = '2020, MOSAIC Group, Sbalzarini Lab, mosaic.mpi-cbg.de'
author = 'MOSAIC Group, Sbalzarini Lab'
# The full version, including alpha/beta/rc tags
release = '1.0.19'
# -- General configuration ---------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['recommonmark',
'sphinx_rtd_theme']
source_suffix = ['.rst', '.md']
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This pattern also affects html_static_path and html_extra_path.
exclude_patterns = []
# -- Options for HTML output -------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
#html_theme = 'alabaster'
html_theme = "sphinx_rtd_theme"
html_theme_options = {
'navigation_depth': 6
}
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
#
# from sphinx.builders.latex import LaTeXBuilder
# LaTeXBuilder.supported_image_types = [
# 'image/svg+xml',
# 'image/tif',
# 'image/png',
# 'image/jpeg'
# ]
from sphinx.builders.html import StandaloneHTMLBuilder
StandaloneHTMLBuilder. supported_image_types = [
'image/svg+xml',
'image/gif',
'image/png',
'image/jpeg'
]
.. _mosaicsuite-development:
=======================
MosaicSuite development
=======================
Source code
===========
MosaicSuite code can be found on public `MOSAIC git server <https://git.mpi-cbg.de/mosaic/MosaicSuite/tree/master>`__.
Code can be downloaded by following git command:
.. code:: bash
git clone https://git.mpi-cbg.de/mosaic/MosaicSuite.git
If you'd like to contribute bug fixes or new functions to any of the plugins, or are interested in using the source code in your own projects, please make sure to first download the latest version. The code is constantly evolving. If you think your additions could be useful also for other users, please send them to us and we will include them in future releases. Your contributions are highly appreciated!
.. MosaicSuite documentation master file
MosaicSuite documentation
=========================
.. note ::
| This documentation is under development. Some parts might be not valid or incomplete.
| In a mean time please refere to `old MosaicSuite documentation <http://mosaic.mpi-cbg.de/MosaicToolboxSuite/MosaicToolsuiteTutorials.html>`__.
**MosaicSuite** is a plugin for popular image processing software *ImageJ2* and *Fiji*.
It provides image-processing algorithms developed at the `MOSAIC group <https://mosaic.mpi-cbg.de>`_.
The first plugin which is now part of MosaicSuite was a popular 2D/3D single-particle tracking tool which can be used to track bright spots in 2D/3D movies over time. As more plugins have been added, we decided to provide them in a single, coherent package, which will also group them under a common menu point ``Plugins->Mosaic`` in ImageJ2 and Fiji.
.. toctree::
:maxdepth: 6
:numbered:
:hidden:
:name: indextoc
:includehidden:
install
news
plugins
development
changelog
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
========================
Installation
========================
Required software
=================
MosaicSuite requires ImageJ2 or Fiji and Java 8 or greater to work.
- How to install Java?
Please download it and install from `official Java site <https://www.oracle.com/java/technologies/>`__.
- How to install Fiji/ImageJ2?
You can download it from `official Fiji site <http://fiji.sc/>`__.
Installation of MosaicSuite plugin
==================================
1. Open Fiji or ImageJ2
#. Run ``Help > Update Fiji`` command (or in case ImageJ2 ``Help > Update...``)
#. Click on ``Manage update sites``
#. Find there and mark ``MOSAIC ToolSuite``
#. Apply changes and Fiji should automatically download latest release of MosaicSuite
#. Restart Fiji (as required) and after restart all functionality by MosaicSuite can be found in ``Plugins > Mosaic`` menu.
.. important::
If you are using very old Java 6 or because any reason you need to install MosaicSuite manually
please refere for detailed instructions `old MosaicSuite site <http://mosaic.mpi-cbg.de/?q=downloads/imageJ>`_.
====
News
====
* **Discrete Region Sampling (DRS)**
Discrete Region Sampling is a sampling version of well known Region Competition algorithm.
It can be found in menu ``Segmentation > Discrete Region Sampling``.
.. admonition:: Citation
| *J. Cardinale*
| Unsupervised Segmentation and Shape Posterior Estimation under Bayesian Image Models. PhD thesis, Diss. ETH No. 21026, MOSAIC Group, ETH Zurich, 2013.
| `PDF <https://mosaic.mpi-cbg.de/docs/Cardinale2013.pdf>`__
*In order to ensure financial support for our project and allow further development of
this software, please cite above publications in all your documents and manuscripts that
made use of this software. Thanks a lot!*
* **Automatic optimal filament segmentation**
The plugin can be used for a globally optimal filament segmentation of 2D images with
previously unknown number of filaments. You can find plugin for segmentation in the menu
``Segmentation > Filament``. Presented solution can produce sub-pixel accuracy results
and handle different types of image data from different microscopy modalities.
The algorithm implemented in this plug-in is described in:
.. admonition:: Citation
| *X. Xiao, V. F. Geyer, H. Bowne-Anderson, J. Howard, and I. F. Sbalzarini.*
| Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets. Med. Image Anal., 32:157–172, 2016.
| `PDF <https://mosaic.mpi-cbg.de/docs/Xiao2016.pdf>`__
*In order to ensure financial support for our project and allow further development of
this software, please cite above publications in all your documents and manuscripts that
made use of this software. Thanks a lot!*
* **Fast implicit curvature filters**
Curvature filters provide geometric means of image filtering, denoising, and restoration.
This amounts to solving a variational model, but the filters here implicitly do this, and
are much faster. You find the filters in the menu ``Enhancement > Curvature Filters``.
Currently, we implement Gauss curvature, Mean curvature, and Total Variation (TV) filters.
The only parameters is the number of iterations, i.e., how many passes of the filter should
be applied to the image. Else the filters are parameter free.
A C++ implementation of these filters is also available `here <https://mosaic.mpi-cbg.de/?q=downloads/curvaturefilters>`__.
The algorithms implemented in this plug-in are described in:
.. admonition:: Citation
| Y. Gong and I. F. Sbalzarini.
| Curvature filters efficiently reduce certain variational energies. IEEE Trans. Image Process., 26(4):1786–1798, 2017.
| `PDF <https://mosaic.mpi-cbg.de/docs/Gong2017.pdf>`__
*In order to ensure financial support for our project and allow further development of
this software, please cite above publications in all your documents and manuscripts that
made use of this software. Thanks a lot!*
* **Image Naturalization**
Image naturalization is an image enhancement technique that is based on gradient statistics
of natural-scence images. The algorithm is completely parameter free. Simply open an image
and choose ``Enhancement > Naturalization`` from the plugin menu. In fluorescence microscopy,
image naturalization can be used for blind deconvolution, dehazing (removing scatter light),
denoising, or contract enhancement. All just with one function! The "naturalness factor"
displayed at the end tells you how close your original image was to a natural-scene one
(1 meaning close, the farther from one the more different).
The algorithm implemented in this plug-in is described in:
.. admonition:: Citation
| Y. Gong and I. F. Sbalzarini.
| Image enhancement by gradient distribution specification. In Proc. ACCV, 12th Asian Conference on Computer Vision, Workshop on Emerging Topics in Image Enhancement and Restoration, pages w7–p3, Singapore, November 2014.
| `PDF <https://mosaic.mpi-cbg.de/docs/Gong2014.pdf>`__
*In order to ensure financial support for our project and allow further development of
this software, please cite above publications in all your documents and manuscripts that
made use of this software. Thanks a lot!*
.. important::
For information about previous news not listed here please refere to `old MosaicSuite site <https://mosaic.mpi-cbg.de/?q=downloads/imageJ>`_.
======================
Particle Tracker 2D/3D
======================
Particle Tracker (PT) is a ImageJ plugin for multiple particle detection and tracking from digital videos
.. figure:: resources/particleTracker/particleTracker.png
:scale: 75 %
:align: center
Particle Tracker in action
General Description
===================
This plugin presents an easy-to-use, computationally efficient, two- and three-dimensional, feature point-tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell biology.
The tracking process requires no apriori mathematical modelling of the motion, it is self-initialising, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region.
The plugin is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. It allows the user to visualize and analyze the detected particles and found trajectories in various ways:
* Preview and save detected particles for separate analysis
* Global non progressive view on all trajectories
* Focused progressive view on individually selected trajectory
* Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to plot particles parameters vs. time - along a trajectory.
Tutorial
========
For detailed description and hints how to use Particle Tracker please refere to :ref:`particletracker-tutorial`.
.. toctree::
:hidden:
particleTrackerTutorial
Developer Resources
===================
Source code and helpful information about MosaicSuite development can be found in :ref:`mosaicsuite-development` section.
Citation
========
.. admonition:: Citation
| *I. F. Sbalzarini and P. Koumoutsakos*
| Feature point tracking and trajectory analysis for video imaging in cell biology. J. Struct. Biol., 151(2): 182-195, 2005.
| `PDF <http://mosaic.mpi-cbg.de/docs/Sbalzarini2005a.pdf>`__
*In order to ensure financial support for our project and allow further development of
this software, please cite above publications in all your documents and manuscripts that
made use of this software. Thanks a lot!*
\ No newline at end of file
This diff is collapsed.
=======
Plugins
=======
.. toctree::
particleTracker
squassh
regionCompetition
=======================
Region Competition (RC)
=======================
Documentation under construction
Citation
========
=======
Squassh
=======
Documentation under construction
Citation
========
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