Machine learning for sperm selection
Infertility rates and the number of couples seeking fertility care have increased worldwide
over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are …
over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are …
Sperm morphology: history, challenges, and impact on natural and assisted fertility
RB Danis, MK Samplaski - Current urology reports, 2019 - Springer
Abstract Purpose of Review The classification of morphologically normal sperm has been
progressively redefined. Concurrently, our understanding of the significance of sperm …
progressively redefined. Concurrently, our understanding of the significance of sperm …
Deep learning for the classification of human sperm
Background Infertility is a global health concern, and couples are increasingly seeking
medical assistance to achieve reproduction. Semen analysis is a primary assessment …
medical assistance to achieve reproduction. Semen analysis is a primary assessment …
Multi-model CNN fusion for sperm morphology analysis
Infertility is a common disorder affecting 20% of couples worldwide. Furthermore, 40% of all
cases are related to male infertility. The first step in the determination of male infertility is …
cases are related to male infertility. The first step in the determination of male infertility is …
Deep learning-based selection of human sperm with high DNA integrity
Despite the importance of sperm DNA to human reproduction, currently no method exists to
assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled …
assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled …
Deep learning-based morphological classification of human sperm heads
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 …
more than 10% of couples across the globe and over 30% of the reported cases are related …
Impact of transfer learning for human sperm segmentation using deep learning
R Marín, V Chang - Computers in Biology and Medicine, 2021 - Elsevier
Background and objective Infertility affects approximately one in ten couples, and almost half
of the infertility cases are due to the malefactor. To diagnose infertility and determine future …
of the infertility cases are due to the malefactor. To diagnose infertility and determine future …
A dictionary learning approach for human sperm heads classification
F Shaker, SA Monadjemi, J Alirezaie… - Computers in biology …, 2017 - Elsevier
Background and objective To diagnose infertility in men, semen analysis is conducted in
which sperm morphology is one of the factors that are evaluated. Since manual assessment …
which sperm morphology is one of the factors that are evaluated. Since manual assessment …
[HTML][HTML] Artificial intelligence for sperm selection—a systematic review
Despite the increasing number of assisted reproductive technologies based treatments
being performed worldwide, there has been little improvement in fertilization and pregnancy …
being performed worldwide, there has been little improvement in fertilization and pregnancy …
Effect of deep transfer and multi-task learning on sperm abnormality detection
A Abbasi, E Miahi, SA Mirroshandel - Computers in Biology and Medicine, 2021 - Elsevier
Analyzing the abnormality of morphological characteristics of male human sperm has been
studied for a long time mainly because it has many implications on the male infertility …
studied for a long time mainly because it has many implications on the male infertility …