Automated Sperm Head Morphology Classification with Deep Convolutional Neural Networks

  • Marco Antônio Calijorne Soares FUMEC University
  • Daniel Henrique Mourão Falci FUMEC University
  • Marco Flávio Alves Farnezi FUMEC University
  • Hana Carolina Moreira Farnezi FUMEC University
  • Fernando Silva Parreiras FUMEC University
  • João Victor Boechat Gomide FUMEC University

Resumo


Background and Objective: The morphological analysis of sperm cells is considered a tool in human fertility prognosis. However, this process is manual, time-consuming and dependent on professional expertise. From a computational perspective, this is a challenging problem due to the high inter-category similarity between the objects of interest and the amount of data available. In this paper, we propose a Convolutional Neural Network model to automate morphology analysis of human sperm heads. Methods: We performed K-Fold cross-validation experiments over two publicly available datasets and assessed the performance of the proposed approach using Accuracy, Precision, Recall and F1-Score. We also compared the proposed model with well-known Convolutional architectures and previous approaches on the same task.Results: Experimental evaluation showed that our approach achieved a macro-averaged F1-score of 0.95 while our best model attained an accuracy of 97.7%. The error analysis revealed a balanced classifier over different sperm head classes. Conclusions: We proved that the proposed approach outperformed the previous state-of-the-art results on this task.
Palavras-chave: Measurement, Head, Image recognition, Computational modeling, Morphology, Computer architecture, Manuals
Publicado
24/10/2022
SOARES, Marco Antônio Calijorne; FALCI, Daniel Henrique Mourão; FARNEZI, Marco Flávio Alves; FARNEZI, Hana Carolina Moreira; PARREIRAS, Fernando Silva; GOMIDE, João Victor Boechat. Automated Sperm Head Morphology Classification with Deep Convolutional Neural Networks. In: CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 35. , 2022, Natal/RN. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 .