A dictionary learning approach for human sperm heads classification.

Journal: Computers in biology and medicine
Published Date: Dec 1, 2017

Abstract

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 of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes. This dictionary is used to classify the sperm heads into four different classes.

Authors

  • Fariba Shaker
    Department of AI, Faculty of Computer Engineering, University of Isfahan, Isfahan, 81746, Iran. Electronic address: f.shaker@eng.ui.ac.ir.
  • S Amirhassan Monadjemi
    Department of AI, Faculty of Computer Engineering, University of Isfahan, Isfahan, 81746, Iran. Electronic address: monadjemi@eng.ui.ac.ir.
  • Javad Alirezaie
    Department of Electrical and Computer Engineering, Ryerson University, Toronto, M5B 2K3, Canada. Electronic address: javad@ryerson.ca.
  • Ahmad Reza Naghsh-Nilchi
    Department of AI, Faculty of Computer Engineering, University of Isfahan, Isfahan, 81746, Iran. Electronic address: nilchi@eng.ui.ac.ir.

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