Windows

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.

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.

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

This is a software toolbox that extends the original BSIF code allowing the utilization of a GPU in Matlab to compute the features. It contains: -Matlab function to calculate BSIF in CPU -Matlab function extension to calculate BSIF in GPU -Pre-learnt filters -Usage instructions

This is a Java content-based image retrieval software components. It can be runned independantly or connected to a Cytomine server. Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based" means that the search algorithm analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image. The term "content" in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. The CBIRetrieval library is: Incremental: You can add new images all over the time. Scalable: Run as many server as you want. Client performs search on all servers. Flexible: Run as a simple app (command line) or use the JAR in your own JVM app/server (java import) Opensource/Free: Apache 2.0 CBIRetrieval is a java library for CBIR, CBIRest is a server with a REST HTTP API with CBIRetrieval embedded. If you want to connect a software/webapp with a CBIR engine, you should use CBIRest. This is a fast multi-threaded and noSQL implementation of the algorithm published in: Incremental Indexing and Distributed Image Search using Shared Randomized Vocabularies Marée, Raphaël; Denis, Philippe; Wehenkel, Louis; Geurts, Pierre,in ACM Proceedings MIR 2010 (2010, March). It was applied on histology images and radiology images.