Computer-assisted system with multiple feature fused support vector machine for sperm morphology diagnosis.

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 onedimensional feature which is extracted from the s...

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Detalles Bibliográficos
Publicado en:	BioMed Research International Vol. 2013; pp. 687607 - 687608
Autores principales:	Tseng, Kuo-Kun, Li, Yifan, Hsu, Chih-Yu, Huang, Huang-Nan, Zhao, Ming, Ding, Mingyue
Formato:	Journal Article
Publicado:	Wiley-Blackwell 2013
Acceso en línea:	Ver este registro en EBSCOhost

Descripción
Sumario:	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 onedimensional 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.