It is able to apply pattern recognition algorithms to two- and three-dimensional biological image sets as well as regions of interest (ROIs) in individual images for automatic classification and annotation. The customizability of BIOCAT is expected to be useful for providing effective and efficient solutions for a variety of biological problems involving image classification and annotation.
A user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfiler for feature extraction.
A simple, user-friendly tool for interactive image classification, segmentation and analysis. It is built as a modular software framework, which currently has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection. Most analysis operations are performed lazily, which enables targeted interactive processing of data subvolumes, followed by complete volume analysis in offline batch mode.
Provides assistance for the analysis of high-throughput microscopy-based screens. imageHTS main features are segmentation of cells, extraction of quantitative cell features, prediction of cell types and visualization of data through web interface. This software offers a standardized access to remote screen data to facilitate the dissemination of high-throughput microscopy-based screens.
It is the ideal "glue" for easily integrating dissimilar fluorescent microscope hardware and peripherals into a single custom workstation, while providing all the tools needed to perform meaningful analysis of acquired images. The software offers many user-friendly application modules for biology-specific analysis such as cell signaling, cell counting, and protein expression.
Provides image analysis tools for segmentation, classification, and downstream analysis of tumour section images. CRImage is a Bioconductor package that allows cellularity scoring of tumours which can then be applied to correct molecular assay data for varying cellularity. It also comes with an algorithm for copy-number data correction given single nucleotide polymorphism (SNP) microarray data and cellular content of the tumours estimated by the image analysis.
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