MotilA: A Python pipeline for microglial fine process motility analysis in 3D time-lapse multiphoton microscopy data

MotilA is an open-source Python pipeline for analyzing microglial fine process motility in time-lapse microscopy datasets. It is developed for multichannel 3D+t multiphoton imaging data and quantifies motility by comparing pixel-based segmentations of z-projected image stacks across consecutive time points.

The pipeline performs image loading, subvolume extraction, optional 2D/3D registration, filtering, histogram adjustment, segmentation and motility quantification. MotilA reports stable, gained and lost pixels, as well as turnover-rate-style motility metrics, and generates visual outputs and tabular result files for single datasets or batch projects.

MotilA uses OMIO, which supports reading TIFF/OME-TIFF, CZI, LSM and Thorlabs RAW files with normalized TZCYX axis handling. It includes example scripts, tutorial notebooks, test data and Read the Docs documentation. It also provides flexible BIDS-like batch discovery and processing, as well as persistent run and error reports.