Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images

	Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images
	Lei Liu; Kai Li; Wenjian Qin; Tiexiang Wen; Ling Li; Jia Wu; Jia Gu
刊名	Medical & Biological Engineering & Computing
	2017
文献子类	期刊论文
英文摘要	Due to the low contrast and ambiguous boundaries of the tumors in breast ultrasound (BUS) images, it is still a challenging task to automatically segment the breast tumors from the ultrasound. In this paper, we proposed a novel computational framework that can detect and segment breast lesions fully automatic in the whole ultrasound images. This framework includes several key components: pre-processing, contour initialization and tumor segmentation. In the pre-processing step, we applied non-local low-rank (NLLR) filter to reduce the speckle noise. In contour initialization step, we cascaded a two-step Otsu-based adaptive thresholding (OBAT) algorithm with morphologic operations to effectively locate the tumor regions and initialize the tumor contours. Finally, given the initial tumor
语种	英语
WOS记录号	WOS:000423726400001
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12005]
专题	深圳先进技术研究院_医工所
作者单位	Medical & Biological Engineering & Computing
推荐引用方式 GB/T 7714	Lei Liu,Kai Li,Wenjian Qin,et al. Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images[J]. Medical & Biological Engineering & Computing,2017.
APA	Lei Liu.,Kai Li.,Wenjian Qin.,Tiexiang Wen.,Ling Li.,...&Jia Gu.(2017).Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images.Medical & Biological Engineering & Computing.
MLA	Lei Liu,et al."Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images".Medical & Biological Engineering & Computing (2017).