Harness deep learning and bounding boxes to perform object detection, segmentation, tracking and more.
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Updated
Jan 24, 2023 - Python
Harness deep learning and bounding boxes to perform object detection, segmentation, tracking and more.
A set of ImageJ plugins to quantify dynamics, morphology, and fluorescence of microglial cells.
Analysis of cell migration in Igor Pro
Trajpy - empowering feature engineering for trajectory analysis across domains.
MigrationmineR is a R package to analyse and profile in vitro cell tracking and migration data. It is belongs to the cytominer-verse used for morphological profiling and allows to create temporal or dynamic profiles.
A Python package for analyzing XYZ positional data of moving objects over time
Metadata for curated CMSO datasets
Proteolytic and non-proteolytic cell migration
Repository for the Minimum Information About Cell Migration Experiments
Automated tracking of cell migration in phase contrast microscope images
Macrophages tracking using phagosight.
Tool for semi-automatic tracking of migrating Dictyostelium cells from phase-contrast time-lapse image series
PIV-based tools for measuring collective cell migration
A Matlab pipeline for spatiotemporal quantification of monolayer cell migration. The repository includes Matlab source code. This repository is part of the book series "Neubias Bioimage Analysis". The analysis pipeline includes segmentation, velocity measurements, kymographs and multi-dimensional representations and PCA of wound healing assays.
Code and supplements to the manuscript "Interpreting T-cell search 'strategies' in the light of evolution under constraints"
This repository enables the reproducible analysis of an important developmental neuroscience dataset on hypothalamus neuron differentiation. It performs quality control, clustering, trajectory analysis, and identification of marker genes to characterize the differentiation trajectories of glutamatergic and GABAergic Onecut3+ neuronal subtypes.
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