Deep Learning-Based Morphological Classification of Human Sperm Heads.

ABSTRACT: Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and subfertility is semen analysis that strongly depends on the sperm head morphology, i.e., the shape and size of the head of a spermatozoon. However, in medical diagnosis, the morphology of the sperm head is determined manually, and heavily depends on the expertise of the clinician. Moreover, this assessment as well as the morphological classification of human sperm heads are laborious and non-repeatable, and there is also a high degree of inter and intra-laboratory variability in the results. In order to overcome these problems, we propose a spec

SUBMITTER: Iqbal I 

PROVIDER: S-EPMC7277990 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature