Bioimage Analysis
Showing 26 of 26 projects
A generalist algorithm for cellular segmentation with human-in-the-loop training and superhuman generalization across diverse microscopy images.
An open-source, plugin-based image processing framework in Python that integrates with numpy-based libraries like scikit-image and OpenCV.
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 vision-language foundation model for computational pathology, pretrained on 1.17M histopathology image-caption pairs for diverse AI tasks.
A deep learning library for single-cell analysis of biological images, specializing in cell segmentation and tracking.
Automated 3D cell detection and classification in large-scale volumetric brain images using deep learning.
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 curated list of software, tools, pipelines, and plugins for image analysis in biological research.
A scalable cell tracking method for 2D, 3D, and multichannel timelapse recordings, robust under segmentation uncertainty.
Interactive exploration and analysis software for large, high-dimensional image-derived biological data with supervised machine learning.
A deep learning-based, threshold-agnostic, subpixel-accurate 2D and 3D spot detection method for fluorescence microscopy and spatial transcriptomics.
A deep learning tool for automatic axon and myelin segmentation from microscopy images using convolutional neural networks.
A tool for cell instance aware segmentation in densely packed 3D volumetric images, originally developed for plant tissues.
A Fiji plugin for pixel-based image segmentation using Weka machine learning algorithms and image features.
A library of mathematical morphology methods and plugins for ImageJ, extending its capabilities for 2D/3D image analysis.
A Python toolbox for analyzing multiplexed imaging data, featuring segmentation, pixel/cell clustering, and spatial analysis.
An automated pipeline for organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy.
A curated list of software, datasets, and publications for image-based profiling of biological phenotypes in drug discovery and cell biology.
A curated list of software, datasets, and publications for image-based profiling of biological phenotypes in drug discovery and cell biology.
A machine learning framework for automated cell segmentation in bioimages using parametric spline curves.
A complete framework for neuronal morphometry, from tracing and reconstruction to analysis, visualization, and modeling.
An open-source tool for precise, interactive, fast, and scalable spot detection in 2D/3D microscopy images for FISH-based spatial genomics.
A 3D convolutional network software package for extracting axonal and filamentous structures from cleared brain imaging data.
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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