title: Acrosome integrity assessment of boar spermatozoa images using an early fusion of texture and contour descriptors.
abstract: The assessment of the state of the acrosome is a priority in artificial insemination centres since it is one of the main causes of function loss. In this work, boar spermatozoa present in gray scale images acquired with a phase-contrast microscope have been classified as acrosome-intact or acrosome-damaged, after using fluorescent images for creating the ground truth. Based on shape prior criteria combined with Otsu's thresholding, regional minima and watershed transform, the spermatozoa heads were segmented and registered. One of the main novelties of this proposal is that, unlike what previous works stated, the obtained results show that the contour information of the spermatozoon head is important for improving description and classification. Other of this work novelties is that it confirms that combining different texture descriptors and contour descriptors yield the best classification rates for this problem up to date. The classification was performed with a Support Vector Machine backed by a Least Squares training algorithm and a linear kernel. Using the biggest acrosome intact-damaged dataset ever created, the early fusion approach followed provides a 0.9913 F-Score, outperforming all previous related works.
authors.affiliation: University of León, Industrial and Informatics Engineering School, 24071 León, Spain. Electronic address: ogaro@unileon.es.
authors.forename: Oscar
authors.initials: O
authors.lastname: García-Olalla
authors.affiliation: University of León, Industrial and Informatics Engineering School, 24071 León, Spain. Electronic address: enrique.alegre@unileon.es.
authors.forename: Enrique
authors.initials: E
authors.lastname: Alegre
authors.affiliation: University of León, Industrial and Informatics Engineering School, 24071 León, Spain. Electronic address: mgaro@unileon.es.
authors.forename: Laura
authors.initials: L
authors.lastname: Fernández-Robles
authors.affiliation: Centre for Image Analysis, Division of Visual Information and Interaction, Uppsala University, Box 337, 751 05 Uppsala, Sweden. Electronic address: patrik.malm@cb.uu.se.
authors.forename: Patrik
authors.initials: P
authors.lastname: Malm
authors.affiliation: Centre for Image Analysis, Division of Visual Information and Interaction, Uppsala University, Box 337, 751 05 Uppsala, Sweden. Electronic address: ewert@cb.uu.se.
authors.forename: Ewert
authors.initials: E
authors.lastname: Bengtsson
mesh_terms: D000177:Acrosome / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D005583:Fourier Analysis; D007091:Image Processing, Computer-Assisted; D007315:Insemination, Artificial; D016018:Least-Squares Analysis; D008297:Male; D008858:Microscopy, Phase-Contrast; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012984:Software; D013077:Sperm Head / Q000502:physiology; D013094:Spermatozoa / Q000502:physiology*; D060388:Support Vector Machine; D013552:Swine
keywords: Acrosome integrity; Contour description; Early fusion; SVM; Texture description