Computer-Assisted System with Multiple Feature Fused Support Vector Machine for Sperm Morphology Diagnosis. (26th September 2013)

• Record Type: Journal Article
• Authors: Tseng, Kuo-Kun; Li, Yifan; Hsu, Chih-Yu; Huang, Huang-Nan; Zhao, Ming; Ding, Mingyue
• Other Names: Chen Lei Academic Editor.
• Is Part Of: BioMed research international. Volume 2013(2013)
• Publication Date: 2013-09-26
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2013/687607
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Sperm morphology is an important technique in identifying the health of sperms. In this paper we present a new system and novel approaches to classify different kinds of sperm images in order to assess their health. Our approach mainly relies on a one-dimensional feature which is extracted from the sperm's contour with gray level information. Our approach can handle rotation and scaling of the image. Moreover, it is fused with SVM classification to improve its accuracy. In our evaluation, our method has better performance than the existing approaches to sperm classification.