Linux

Description

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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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Description

This is a Matlab implementation of Local Phase Quantization (LPQ) texture descriptors that is robust to image blurring due to the use of phase information. Theoretical background could be found here: http://www.ee.oulu.fi/research/mvmp/mvg/files/pdf/ICISP08.pdf

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Description

ASAP is an open source platform for visualizing, annotating and automatically analyzing whole-slide histopathology images. It consists of several key-components (slide input/output, image processing, viewer) which can be used seperately. It is built on top of several well-developed open source packages like OpenSlide, Qt and OpenCV but also tries to extend them in several meaningful ways.

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Description

MyTardis is free and open-source data management software. It facilitates annotation, sharing and archiving of data and metadata collected from different modalities. It focuses on integration with scientific instruments, instrument facilities and research storage and computing infrastructure; to address the challenges of data storage, data access, collaboration and data publication. It is currently being used to capture data from areas such as optical microscopy, electron microscopy, medical imaging, protein crystallography, neutron and X-ray scattering, flow cytometry, genomics and proteomics.

Key features:

  • Easy instrument integration.
  • Discipline specific: MX, Imaging, Microscopy, Genomics ...
  • Wide range of data formats & supported instruments.
  • Secure cloud data storage & access.
  • Simple data sharing.
  • Researcher controlled data publishing.
  • APIs for programmatic access to data and metadata.
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Description

QuPath is open source software for Quantitative Pathology. QuPath has been developed as a research tool at Queen's University Belfast.

QuPath