Metadata-Version: 2.4
Name: cytoscan
Version: 0.1.0
Summary: Cell migration analysis for microfluidic ATPS channels
Author-email: Mateo McKee <mateomckee64@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/mateomckee/cytoscan
Project-URL: Repository, https://github.com/mateomckee/cytoscan
Project-URL: Issues, https://github.com/mateomckee/cytoscan/issues
Keywords: microscopy,cell-tracking,microfluidics,image-analysis
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.24
Requires-Dist: scipy>=1.11
Requires-Dist: opencv-python>=4.8
Requires-Dist: matplotlib>=3.7
Requires-Dist: pyyaml>=6
Requires-Dist: pydantic>=2
Dynamic: license-file

# cytoscan

Cell migration analysis for microfluidic ATPS channels. Detects cells,
channel walls, and the membrane interface from brightfield + fluorescent
microscopy frames; produces per-cell distance and category data.

## Install

    pip install cytoscan

## Usage

    cytoscan init my_experiment           # scaffold dir + config
    # drop tifs (br/fl/mx triples) into my_experiment/
    cytoscan run my_experiment            # full pipeline
    cytoscan validate my_experiment       # detection-only, with flag table
    cytoscan version

Outputs land in `my_experiment/output/`:
- `cells.csv`, `frames.csv`, `interface.csv`, `summary.txt`
- `output_frame*.png` (visual overlays)

Built for the Sun Lab — https://www.sunlabutsa.org/
by Mateo McKee
