Deep learning-based automatic image classification of oral cancer cells acquiring chemoresistance in vitro.

ABSTRACT: Cell shape reflects the spatial configuration resulting from the equilibrium of cellular and environmental signals and is considered a highly relevant indicator of its function and biological properties. For cancer cells, various physiological and environmental challenges, including chemotherapy, cause a cell state transition, which is accompanied by a continuous morphological alteration that is often extremely difficult to recognize even by direct microscopic inspection. To determine whether deep learning-based image analysis enables the detection of cell shape reflecting a crucial cell state alteration, we used the oral cancer cell line resistant to chemotherapy but having cell morphology nearly indiscernible from its non-resistant parental cells. We then implemented the automatic approa

SUBMITTER: Hsieh HC 

PROVIDER: S-EPMC11530068 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature