Machine learning models for segmentation and classification of cyanobacterial cells.

ABSTRACT: Timelapse microscopy has recently been employed to study the metabolism and physiology of cyanobacteria at the single-cell level. However, the identification of individual cells in brightfield images remains a significant challenge. Traditional intensity-based segmentation algorithms perform poorly when identifying individual cells in dense colonies due to a lack of contrast between neighboring cells. Here, we describe a newly developed software package called Cypose which uses machine learning (ML) models to solve two specific tasks: segmentation of individual cyanobacterial cells, and classification of cellular phenotypes. The segmentation models are based on the Cellpose framework, while classification is performed using a convolutional neural network named Cyclass. To our knowledge, th

SUBMITTER: Huffine CA 

PROVIDER: S-EPMC11807057 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature