GEMA – An Automatic Segmentation Method for Real- Time Analysis of Mammalian Cell Growth in Microfluidic Device

RAMIRO ISA-JARA; CAMILO PÉREZ-SOSA; ERICK MACOTE-YPARRAGUIRRE; NATALIA REVOLLO; BETIANA LERNER; MIRIUKA, SANTIAGO; MAXIMILIANO PÉREZ; ROLAND MERTELSMANN

Freiburg

Congreso; Intelligent Oncology CRIION. Best Poster Award; 2022

MCF7 (Michigan Cancer Foundation-7) cells are used to model their growth and dead when they have been injected with some drug. These mammalian cells allow understanding of behavior, gene expression, and drug resistance to breast cancer. For this, an automatic segmentation method called GEMA (Gaborfilter in biological experiments with morphology operations for segmentation applications) is presented to analyze the apoptosis and confluence stages of culture by measuring the increase or decrease of the image area occupied by cells in microfluidic devices. GEMA allows the processing of images in real time during the evolution of biological experiments. Moreover, it has been compared with another three representative methods such as gold standard (manual segmentation), morphological gradient, and a semi-automatic algorithm using FIJI.