High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition
Sperm cell motility and morphology observed under the bright fieldmicroscopy are the only criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) procedure of Assisted ReproductiveTechnology (ART). Several factors such as oxidative stress, cryopreservation, heat, smoking and alcohol consumption, are negatively associated with the quality of sperm cell and fertilization potential due to the changing of subcellular structures and functions which are overlooked. We developed a partially spatially coherent digital holographic microscope (PSC-DHM) for quantitative phase imaging (QPI) in order to distinguish normal sperm cells from sperm cells under different stress conditions. Total of seven feedforward deep neural networks (DNN) are employed for the classification of the phase maps for normal and stress affected sperm cells.
Nature Scientific Reports: https://www.nature.com/articles/s41598-020-69857-4
Ankit Butola, Prof. P. Senthilkumaran and Prof. Dalip Singh Mehta