A semi-automatic method for robust and efficient identification of neighboring muscle cells

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	A semi-automatic method for robust and efficient identification of neighboring muscle cells
	Wang ZZ(王振洲)
刊名	Pattern Recognition
	2016
卷号	53 页码:300-312
关键词	Segmentation Threshold selection Morphological erosion Morphological dilation Muscle cell/fiber
ISSN号	0031-3203
通讯作者	王振洲
产权排序	1
中文摘要	Segmentation and identification of muscle cells robustly and efficiently is of considerable importance in determining the muscle's physiological conditions. It is challenging due to frequently occurring artifacts, indistinct boundary between adjacent cells, the arbitrary shape and large number of cells. Currently, the widely used segmentation and quantification tools are usually manual or semi-automatic, which is time-consuming and labor intensive. In this paper, a semi-automatic method is proposed to segment the muscle cells robustly and efficiently. The proposed approach utilizes and evolves three fundamental image processing techniques, threshold selection, morphological ultimate erosion and morphological dilation. Experimental results verified the effectiveness of the proposed method.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	RESTRICTED EQUIVALENCE FUNCTIONS ; IMAGE SEGMENTATION ; FUZZY-SETS ; AUTOMATED SEGMENTATION ; MEMBERSHIP FUNCTIONS ; SELECTION METHOD ; FIBER IMAGES ; MICROSCOPY ; RECOGNITION ; CONTOURS
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000370885700023
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/17616]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Wang ZZ. A semi-automatic method for robust and efficient identification of neighboring muscle cells[J]. Pattern Recognition,2016,53:300-312.
APA	Wang ZZ.(2016).A semi-automatic method for robust and efficient identification of neighboring muscle cells.Pattern Recognition,53,300-312.
MLA	Wang ZZ."A semi-automatic method for robust and efficient identification of neighboring muscle cells".Pattern Recognition 53(2016):300-312.