M-Phase Feature Extraction Algorithm for Phenotype Classification from Cancer Brightfield Microscopy

Abstract

In this paper a workflow to extract cell features from brightfield microscopy image sequences is proposed. An event driven approach, combined with a forward and backward tracking limited by the cell's circularity was proven enough to extract relevant features that can be used to classify the cells into four phenotypes related to chemosensitivity studies: cell cycle arrest, apoptotic, damage proliferation and cells that have repaired their DNA damage. An average F1-Score greater than 0.7 was achieved in the detection and follow up of the events on images that present characteristics that impede the use of classic image segmentation and methods.