Imaging

Ultrack is a versatile and scalable cell tracking method designed to address the challenges of tracking cells across 2D, 3D, and multichannel timelapse recordings, especially in complex and crowded tissues where segmentation is often ambiguous. By evaluating multiple candidate segmentations and employing temporal consistency, Ultrack ensures robust performance under segmentation uncertainty. Ultrack's methodology is explained here.

(from https://github.com/royerlab/ultrack)

The BioVoxxel Toolbox is a suite which contains plugins and some macros dealing with image filtering, image segmentation and binary image processing and analysis. The following plugins are hosted here:

• Extended Particle Analyzer
• Binary Feature Extractor
• Speckle Inspector
• Watershed Irregular Features
• EDM Binary Operations
• Filter Check
• Pseudo flat-field correction
• Convoluted Background Subtraction
• 2D Particle Distribution (Distribution_Analysis)
• Cluster Indicator
• SSIDC Cluster Indicator
• Gaussian weighted Median filter
• Adaptive Filter
• Enhance True Color Contrast
• Mode and Differential Limited Mean Binarization
• Basic Recursive Filter

TissUUmaps is a browser-based tool for fast visualization and exploration of millions of data points overlaying a tissue sample. TissUUmaps can be used as a web service or locally in your computer, and allows users to share regions of interest and local statistics.

MATLAB app to characterize nanoparticles imaged with super-resolution microscopy. nanoFeatures will read text and csv files from the NIKON and ONI microscopes and from the ThunderSTORM Fiji plugin, then cluster the localizations and filter by size and sphericity and finally output nanoparticle features like size, aspect ratio, and number of localizations per cluster (total and for each channel).

Machine Learning made easy

APEER ML provides an easy way to train your own machine learning
models and segment your microscopy images. No expertise or coding required.