Cell Segmentation
Showing 13 of 13 projects
A generalist algorithm for cellular segmentation with human-in-the-loop training and superhuman generalization across diverse microscopy images.
A Python library for 2D/3D object detection and instance segmentation in microscopy images using star-convex shapes.
Interactive segmentation and tracking tools for microscopy images built on Segment Anything.
A deep learning library for single-cell analysis of biological images, specializing in cell segmentation and tracking.
A semi-automated pipeline for instance-aware cell segmentation, tracking, and migration analysis in phase contrast microscopy using Mask R-CNN.
A foundation model for cell segmentation that achieves state-of-the-art performance across diverse cellular targets and imaging modalities.
A scalable cell tracking method for 2D, 3D, and multichannel timelapse recordings, robust under segmentation uncertainty.
A probabilistic cell segmentation method for spatial transcriptomics data from platforms like Xenium, CosMx, MERSCOPE, and Visium HD.
A tool for cell instance aware segmentation in densely packed 3D volumetric images, originally developed for plant tissues.
A Python toolbox for analyzing multiplexed imaging data, featuring segmentation, pixel/cell clustering, and spatial analysis.
A Python toolbox for analyzing smFISH microscopy images, including spot detection and cell segmentation.
A machine learning framework for automated cell segmentation in bioimages using parametric spline curves.
A foundation model-driven method for semantic cell classification in whole slide images, extending Cellpose with a WSI workflow and QuPath integration.
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