pystackreg

Description

Python/C++ port of the ImageJ extension TurboReg/StackReg written by Philippe Thevenaz/EPFL.

A python extension for the automatic alignment of a source image or a stack (movie) to a target image/reference frame.

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elastix

Description

Elastix is a toolbox for rigid and nonrigid registration of (medical) images.

Elastix is based on the ITK library, and provides additional algorithms for image registration. 

The software can be run as a single-line command, making it easy to include in larger scripts or workflows. The user needs to edit a configuration file that contains all relevant parameters for registration: transformation model, metric used to comapre images, optimization algorithm, mutliscale pyramidal representation of images...

Nowadays elastix is accompanied by SimpleElastix, making it available in other languages like C++, Python, Java, R, Ruby, C# and Lua.

elastix logo

Fiji CMTK GUI

Description

Working version of a simple GUI frontend for CMTK image registration tools in Fiji

has topic
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ANTs: Advanced Normalization Tools

Description

ANTs computes high-dimensional mappings to capture the statistics of brain structure and function.

Image Registration

Diffeomorphisms: SyN, Independent Evaluation: Klein, Murphy, Template Construction (2004)(2010), Similarity Metrics, Multivariate registration, Multiple modality analysis and statistical bias

Image Segmentation

Atropos Multivar-EM Segmentation (link), Multi-atlas methods (link) and JLF, Bias Correction (link), DiReCT cortical thickness (link), DiReCT in chimpanzees

 

Advanced Normalization Tools

CMTK

Description

A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O.

The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction; EPI unwarping), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear model).

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Multiview Reconstruction

Description

The Multiview Reconstruction software package enables users to register, fuse, deconvolve and view multiview microscopy images. The software is designed for lightsheet fluorescence microscopy (LSFM), but is applicable to any form of three or higher dimensional imaging modalities like confocal timeseries or multicolor stacks. 

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BigDataViewer

Description

The BigDataViewer is a re-slicing browser for terabyte-sized multi-view image sequences. BigDataViewer was developed with multi-view light-sheet microscopy data in mind and integrates well with Fiji's SPIMage processing pipeline.

BigStitcher

Description

The BigStitcher is a software package that allows simple and efficient alignment of multi-tile and multi-angle image datasets, for example acquired by lightsheet, widefield or confocal microscopes. The software supports images of almost arbitrary size ranging from very small images up to volumes in the range of many terabytes, which are for example produced when acquiring cleared tissue samples with lightsheet microscopy.

performing automatic registration for CLEM

Description

This is an example workflow of how to perform automatic registration by

- first detecting spots in both image using wavelet segmentation (with different scale according to the image scale)

- second using Ec-Clem autofinder to register both images

Click on a block to know more about a tool. Non referenced tools are non clickable.

testWorkflowtestWorkflowtestWorkflowimage map example
Workflow results

simpleElastix

Description

quote:

Elastix cite{Klein2010} is an open source, command-line program for intensity-based registration of medical images that allows the user to quickly configure, test, and compare different registration methods. SimpleElastix is an extension of SimpleITK cite{Lowekamp2013} that allows you to configure and run Elastix entirely in Python, Java, R, Octave, Ruby, Lua, Tcl and C# on Linux, Mac and Windows. The goal is to bring robust registration algorithms to a wider audience and make it easier to use elastix, e.g. for Java-based enterprise applications or rapid Python prototyping.

Python example

import SimpleITK as sitk
resultImage = sitk.Elastix(sitk.ReadImage("fixedImage.nii"), sitk.ReadImage("movingImage.nii"))