Sperm cell segmentation in digital micrographs based on convolutional neural networks using U-net architecture

Roy Melendez, Cesar Beltran Castanon, Rosario Medina-Rodriguez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Human infertility is considered a serious disease of the reproductive system that affects more than 10% of couples worldwide, and more than 30% of reported cases are related to men. The crucial step in evaluating male infertility is a semen analysis, highly dependent on sperm morphology. However, this analysis is done at the laboratory manually and depends mainly on the doctor's experience. Besides, it is laborious, and there is also a high degree of interlaboratory variability in the results. This article proposes applying a specialized convolutional neural network architecture (U-Net), which focuses on the segmentation of sperm cells in micrographs to overcome these problems. The results showed high scores for the model segmentation metrics such as precision (93%), IoU score (88%), and DICE score of 94%. Moreover, we can conclude that U-net architecture turned out to be a good option to carry out the segmentation of sperm cells.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2021 IEEE 34th International Symposium on Computer-Based Medical Systems, CBMS 2021
EditoresJoao Rafael Almeida, Alejandro Rodriguez Gonzalez, Linlin Shen, Bridget Kane, Agma Traina, Paolo Soda, Jose Luis Oliveira
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas91-96
Número de páginas6
ISBN (versión digital)9781665441216
DOI
EstadoPublicada - jun. 2021
Evento34th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2021 - Virtual, Online
Duración: 7 jun. 20219 jun. 2021

Serie de la publicación

NombreProceedings - IEEE Symposium on Computer-Based Medical Systems
Volumen2021-June
ISSN (versión impresa)1063-7125

Conferencia

Conferencia34th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2021
CiudadVirtual, Online
Período7/06/219/06/21

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