QuPath - Bioimage analysis & digital pathology
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Updated
Aug 6, 2024 - Java
QuPath - Bioimage analysis & digital pathology
StarDist plugin for napari
Cell tracking and segmentation software
imageC / EVAnalyzer2 - High throughput biological image processor
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
Spatiotemporal modeling of spatial transcriptomics
Segment Anything for Microscopy
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]
[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
ClusterMap for multi-scale clustering analysis of spatial gene expression
Registration of cells across sessions.
Generate consensus 3D cells segmentations by combining 2D cell segmentations from any combination of xy, xz, yz views, compatible with outputs of any 2D segmentation method.
This project implements cell segmentation and classification of red and white blood cells using the YOLOv8 model.
StarDist - Object Detection with Star-convex Shapes
Scalable Instance Segmentation using PyTorch & PyTorch Lightning.
Deep-Learning enabled quantitative image analysis of for the yeast full life cycle
SuperDSM is a globally optimal segmentation method based on superadditivity and deformable shape models for cell nuclei in fluorescence microscopy images and beyond.
This repository is dedicated to the segmentation of histological features in regenerated vascular tissues obtained from tissue-engineered vascular grafts (TEVGs) implanted in sheep.
Encoder-Decoder Cell and Nuclei segmentation models
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