NDLI: Ultrasound lesion segmentation using clinical knowledge-driven constrained level set

Content Provider	IEEE Xplore Digital Library
Author	QiZhong Lin Liu, S. Parajuly, S.S. Yinhui Deng Boroczky, L. Sainan Fu Ying Wu Yulan Pen
Copyright Year	2013
Description	Author affiliation: Philips Res. Asia Shanghai, Shanghai, China (QiZhong Lin; Yinhui Deng; Sainan Fu; Ying Wu) \|\| Dept. of Ultrasound, Western China Hosp., Chengdu, China (Parajuly, S.S.; Yulan Pen) \|\| Philips Res. North America, Briarcliff Manor, NY, USA (Liu, S.; Boroczky, L.)
Abstract	Ultrasound lesion segmentation is an important and challenging task. Comparing with other methods, region-based level set has many advantages, but still requires considerable improvement to deal with the characteristic of lesions in the ultrasound modality such as shadowing, speckle and heterogeneity. In the clinical workflow, the physician would usually denote long and short axes of a lesion for measurement purpose yielding four markers in an image. Inspired by this workflow, a constrained level set method is proposed to fully utilize these four markers as prior knowledge and global constraint for the segmentation. First, the markers are detected using template-matching algorithm and B-Spline is applied to fit four markers as the initial contour. Then four-marker constrained energy is added to the region-based local level set to make sure that the contour evolves without deviation from the four markers. Finally the algorithm is implemented in a multi-resolution scheme to achieve sufficient computational efficiency. The performance of the proposed segmentation algorithm was evaluated by comparing our results with manually segmented boundaries on 308 ultrasound images with breast lesions. The proposed method achieves Dice similarity coefficient 89.49±4.76% and could be run in real-time.
Starting Page	6067
Ending Page	6070
File Size	777520
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610936
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lesions Ultrasonic imaging Image segmentation Breast Level set Manuals
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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