Classification of human spermatozoa using quantitative phase imaging and machine learning

Autor:	P. Senthilkumaran, Daria Popova, Purusotam Banet, Ankit Butola, Dalip Singh Mehta, Balpreet Singh Ahluwalia, Vishesh Dubey, Ganesh Acharya, Azeem Ahmad
Rok vydání:	2019
Předmět:	Quantitative phase microscopy business.industry education Maximum phase Machine learning computer.software_genre Phase unwrapping Sperm Phase map Phase imaging Phase noise Microscopy Artificial intelligence business computer Mathematics
Zdroj:	Digital Holography and Three-Dimensional Imaging 2019.
Popis:	Quantitative phase microscopy is used to determine phase map of human sperm cells and found that the maximum phase value decreases under oxidative stressed conditions. Machine learning is used to classify various parameters.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a5934b9218cade98cb890e93b0ad06a9 https://doi.org/10.1364/dh.2019.th4a.3 Zobrazit plný text záznamu