Utilizing different imaging modalities in combination

Image registration in Matlab with Image Processing Toolbox

Description

Align two images using intensity correlation, feature matching, or control point mapping

Together, Image Processing Toolbox™ and Computer Vision Toolbox™ offer four image registration solutions: interactive registration with a Registration Estimator app, intensity-based automatic image registration, control point registration, and automated feature matching. 

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DragonFly

Description

Dragonfly is a software platform for the intuitive inspection of multi-scale multi-modality image data. Its user-friendly experience translates into powerful quantitative findings with high-impact visuals, driven by nuanced easy-to-learn controls.

For segmentation: It provides an engine fior machine Learning, Watershed and superpixel methods, support histological data .

It offers a 3D viewer, and python scripting capacities .

It is free for reserach use, but not for commercial usage.

DragonFly

BIRL: Benchmark on Image Registration methods with Landmark validation

Description

The project introduces a cross-platform framework for comparison of image registration methods with landmark validation (registration precision is measured by user landmarks). The project contains a set of sample images with related landmark annotations and experimental evaluation of state-of-the-art image registration methods.

Some key features of the framework:

  • automatic execution of image registration of a sequence of image pairs
  • integrated evaluation of registration performances using Target Registration Error (TRE)
  • integrated visualization of performed registration
  • running several image registration experiment in parallel
  • resuming unfinished sequence of registration benchmark
  • handling around dataset and creating own experiments
  • rerun evaluation and visualisation for finished experiments
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Registrationshop

Description

It is an interactive front-end visualization for registration software based on Elasix (VTK/ITK)

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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.

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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"))
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eC-CLEM

Description

This plugin allows to compute a similarity (translation/rotation/scaling and flipping) transform from pair of points. It is updating the transformed image interactively such that the user get immediate feedback. The transformation is saved and can be applied to any other stack/image. Non rigid deformation can also be applied in 2D or 3D.

3D/3D,2D/3D or 3D /2D can be handled .

3D ROI are enabled, and can be checked with the 3D vtk view (size of ROI can be changed using the ROI stroke width).

Some prealignment by rotating in 3D the volume is possible.

Transformations can be applied directly or combined through Block Protocols (search for apply transformation).

It's also provide information about the predicted Error (based on statistical prediction), either as a full color mapping, either on each points used as landmarks, and error on the discrepancy in position between points.

There are video tutorials available in the web.

 

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Amira

Description

Amira is 3D visualization and analysis software for life sciences.
 

" Amira software is a powerful, multifaceted 3D platform for visualizing, manipulating, and understanding life sciences data from computed tomography, microscopy, MRI, and many other imaging modalities. 
With incredible speed and flexibility, Amira software enables advanced 3D imaging workflows for specialists in research areas ranging from molecular and cellular biology to neuroscience and bioengineering. "

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Amira's interface

IMOD

Description

IMOD is a set of image processing, modeling and display programs used for tomographic reconstruction and for 3D reconstruction of EM serial sections and optical sections. The package contains tools for assembling and aligning data within multiple types and sizes of image stacks, viewing 3-D data from any orientation, and modeling and display of the image files.

Included are two programs with graphical interface: 3dmod, for displaying and segmenting 2D images and 3D volumes; etomo, for reconstructing tomographic volumes from tilt series of images.

Processing can be distributed on multiple cores and executed in batch mode.

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iMod

Imaris

Description

Imaris is a software for data visualization, analysis, segmentation and interpretation of 3D and 4D microscopy images. It performs interactive volume rendering that lets users freely navigate even very large datasets (hundreds of GB). It performs both manual and automated detection and tracking of biological “objects” such as cells, nuclei, vesicles, neurons, and many more. ImarisSpots for example is a tool to detect “spherical objects” and track them in time series. Besides the automated detection it gives the user the ability to manually delete and place new spots in 3D space. ImarisCell is a tool to detect nuclei, cell boundaries and vesicles and track these through time. ImarisFilament is a module that lets users trace neurons and detect spines. For any detected object Imaris computes a large set of statistics values such as volume, surface area, maximum intensity of first channel, number of vesicles per cell etc. These values can be exported to Excel and statistics software packages. The measurements can also be analyzed directly within ImarisVantage which is a statistics tool that provides the link back to the 3D objects and the original image data. Strengths: - good visualization - user friendly interface - reads most microscopy file formats - image analysis workflows are very easy to apply - interactive editing of objects to correct errors during automatic detection - large data visualization (hundreds of GB)

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