Cellects

Cellects automatically quantifies biological growth, motion, and morphology from 2D image data and time-lapse sequences (2D + t) across diverse biological systems and experimental conditions.

Key Features:

• Multi-organism analysis: Supports single or multiple organisms growing or moving in one or several arenas, with sequential analysis of multiple folders.
• Geometrical descriptors: Extracts area, circularity, orientation axes, centroid trajectories, oscillations, and network topology.
• Flexible input processing: Handles grayscale or color images from standard microscopy, macroscopic imaging setups, or camera-based platforms.
• Standardized output: Exports all quantitative results as .csv files for downstream statistical analysis and workflow integration.
• Extensible pipeline: Analysis pipeline can be extended and customized using a dedicated Python API.

Scientific Applications:

• Fungal colony growth: Quantifies expansion dynamics in fungal colonies from 2D time-lapse imaging.
• Unicellular branching networks: Analyzes morphology and network topology in unicellular branching organisms.
• Motion tracking: Measures centroid trajectories and oscillations to characterize organism movement.

Methodology:

Automated image analysis pipeline for 2D and 2D + t data; specific computational steps are not explicitly detailed in the sources.