cell-tracking

Bayesian multi-object tracking

Cell tracking and segmentation software

A python algorithm for tracking cells in 3D deforming organs

Track and lineage visualization with btrack and Napari 🌲

Automated batch processing of cell and tissue microscopy image data in Napari

Explainable AI model of cell behavior

A common data structure and basic tools for multi-object tracking.

Harness deep learning and bounding boxes to perform object detection, segmentation, tracking and more.

Microscopy image processing with TensorFlow

Napari plugin and other code for BC-FLIS

A Napari plugin for automated cell nuclei detection, cell proliferation & population growth analysis, and single-cell tracking in brightfield and fluorescence microscopy images

Automated sperm motility analysis pipeline with OpenCV-based detection and standard motility parameter calculations (VCL, VSL, VAP). Features motion-aware cascade matching and batch processing

Generalized and streamlined image phenotyping of dynamic objects over time

CellScope detects cell boundaries, tracks cells across frames, and quantifies migration, morphology, and edge dynamics — with support for both single-cell and multi-cell recordings. It provides a complete GUI-based workflow from raw recordings to publication-ready figures and statistical comparisons.

A napari plugin combining fluorescence microscopy with impedance imaging for cellular analysis.

An automated, open-source pipeline for tracking cellular expansion / shrinkage in microscopy timelapses using Cellpose.

Knime workflow to facilitate segmentation and tracking in 3D + time cell images using the TGMM 1.0 software by the Keller lab (https://www.janelia.org/lab/keller-lab).

Deep Learning based segmentation and tracking to understand the dynamics and morphology of cells over time.

Kaggle entry for Biohub – Cell Tracking During Development: 3D+time cell tracking in zebrafish embryo microscopy via U-Net + transformer + ILP with graph repair. Public LB 0.817.

Viewer and analysis workbench for CellScope results - inspect tracked cells, quantify shape, motility and edge dynamics, compare treatments across recordings, and export tidy CSV. PyQt5 + pyqtgraph, CPU-only.