TY  - JOUR
T1  - Automatic Assessment of Human Sperm Images with Capsule Networks
AU  - Şen, Mert
AU  - Doğan, Hatice
PY  - 2021
DA  - January
JF  - Natural and Applied Sciences Journal
JO  - IDU Natural and Applied Sciences Journal (IDUNAS)
PB  - Izmir University of Democracy
WT  - DergiPark
SN  - 2645-9000
SP  - 62
EP  - 70
VL  - 3
IS  - Special Issue: Full Papers of 2nd International Congress of Updates in Biomedical Engineering
LA  - en
AB  - Infertility which is a psychologically threatening and emotionally stressful problem is seen approximately 15% of couples in worldwide. Recent studies have shown that in 40-50% of couples evaluated for infertility, the problem is caused by the male individual. Sperm morphology analysis that provides separation of normal and abnormal sperm is very important in evaluating male infertility and showing the causes. Since manual evaluation of sperm morphology is time consuming and subjective, automatic assessment methods are needed. In this study, Capsule Networks, a special model of Deep Neural Networks (DNN), are used for the classification of human sperm head images. The classification performances of capsule networks are measured using the Modified Human Sperm Morphology Analysis dataset (MHSMA). The results show that the best classification accuracy is achieved as 73%.
KW  - Capsule networks
KW  - infertility
KW  - sperm morphology
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UR  - https://dergipark.org.tr/en/pub/idunas/issue//862546
L1  - https://dergipark.org.tr/en/download/article-file/1513820
ER  -