Contents

GelBandFitter is a user-friendly software specific for analysis of protein gels and estimation of relative protein content. Using non-linear regression methods to fit mathematical functions to densitometry profiles, it is able to estimate content from protein bands that partially overlap. The software is available either as Matlab code (Optimization toolbox required) or a Windows executable. Reference: Mitov, M. I., Greaser, M. L., & Campbell, K. S. (2009). GelBandFitter – A computer program for analysis of closely spaced electrophoretic and immunoblotted bands.

SRRF is a high-performance analytical approach for Live-cell Super-Resolution Microscopy, provided as a fast GPU-enabled ImageJ plugin. SRRF is capable of extracting high-fidelity super-resolution information from TIRF, widefield and confocals using conventional fluorophores such as GFP. SRRF is capable of live-cell imaging over timescales ranging from minutes to hours.

Spotsizer is a software tool that automates analysis of large volumes of photographic images of growing microbes.

CellProfiler is free, open-source software for quantitative analysis of biological images.

PopulationProfiler – is light-weight cross-platform open-source tool for data analysis in image-based screening experiments. The main idea is to reduce per-cell measurements to per-well distributions, each represented by a histogram. These can be optionally further reduced to sub-type counts based on gating (setting bin ranges) of known control distributions and local adjustments to histogram shape. Such analysis is necessary in a wide variety of applications, e.g.

BioImageXD is a free open source software package for analyzing, processing and visualizing multi-dimensional microscopy images. It's a collaborative project, designed and developed by microscopists, cell biologists and software engineers from the Universities of Jyväskylä and Turku in Finland, Max Planck Institute CBG in Dresden, Germany and collaborators worldwide. BioImageXD was published in the July 2012 issue of Nature Methods.

ADAPT is capable of rapid, automated analysis of migration and membrane protrusions, together with associated
fluorescently labeled proteins, across multiple cells. ADAPT can detect and morphologically profile filopodia.

Advanced Cell Classifier is a data analyzer program to evaluate cell-based high-content screens and tissue section images developed at the Biological Research Centre, Szeged and FIMM, Helsinki (formerly at ETH Zurich). The basic aim is to provide a very accurate analysis with minimal user interaction using advanced machine learning methods.

A standalone cell tracking software for single cell migration. Tracking of cells in tissue was also done in Drosophila germband.

The ImageJFX Project aims to create a new user interface for the software ImageJ in order to ease scientific image analysis. While keeping the core components of ImageJ, ImageJFX brings scientists closer to their goal by making the interface clearer for beginners and more practical for advanced users.

QuantCenter is the framework for 3DHISTECH image analysis applications. with the goal of helping the pathologists to diagnose in an easier way. QuantCenter, is optimized for whole slide quantification. It has a linkable algorithm concept that tries to provide an easy-to-use and logical workflow. The user has different quantification modules that he or she could link one after other to fine-tune or to speed up the analysis.

COLORLAB is a component for processing, representing and reproducing color in a MATLAB environment. Among others, some of the functionalities it makes able to: -Represent the color content of any image in chromatic diagrams and tristimulus spaces in any system of primaries. -Compute advanced color descriptions of any image using several color appearance models (CIELab, CIEluv, ATD, Rlab, LLab, SVF and CIECAM). An userguide is provided.

We propose to use a kernel density estimation (KDE) based approach for classification. This non-parametric approach intrinsically provides the likelihood of membership for each class in a principled manner. The implementation was used in Ghani2016. Any papers using this code should cite Ghani2016 accordingly. The software has been tested under Matlab R2013b.

Sample Data: Annotated two-photon images of dendritic spines

quote:

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

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.

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.