Robust vessel detection and segmentation in ultrasound images by a data-driven approach

Ping Guo; Qiang Wang; Xiaotao Wang; Zhihui Hao; Kuanhong Xu; Haibing Ren; Jung Bae Kim; Youngkyoo Hwang

doi:10.1117/12.2042973

21 March 2014 Robust vessel detection and segmentation in ultrasound images by a data-driven approach

Ping Guo, Qiang Wang, Xiaotao Wang, Zhihui Hao, Kuanhong Xu, Haibing Ren, Jung Bae Kim, Youngkyoo Hwang

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 903435 (2014) https://doi.org/10.1117/12.2042973
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

This paper presents a learning based vessel detection and segmentation method in real-patient ultrasound (US) liver images. We aim at detecting multiple shaped vessels robustly and automatically, including vessels with weak and ambiguous boundaries. Firstly, vessel candidate regions are detected by a data-driven approach. Multi-channel vessel enhancement maps with complement performances are generated and aggregated under a Conditional Random Field (CRF) framework. Vessel candidates are obtained by thresholding the saliency map. Secondly, regional features are extracted and the probability of each region being a vessel is modeled by random forest regression. Finally, a fast levelset method is developed to refine vessel boundaries. Experiments have been carried out on an US liver dataset with 98 patients. The dataset contains both normal and abnormal liver images. The proposed method in this paper is compared with a traditional Hessian based method, and the average precision is promoted by 56 percents and 7.8 percents for vessel detection and classification, respectively. This improvement shows that our method is more robust to noise, therefore has a better performance than the Hessian based method for the detection of vessels with weak and ambiguous boundaries.

Citation Download Citation

Ping Guo, Qiang Wang, Xiaotao Wang, Zhihui Hao, Kuanhong Xu, Haibing Ren, Jung Bae Kim, and Youngkyoo Hwang "Robust vessel detection and segmentation in ultrasound images by a data-driven approach", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903435 (21 March 2014); https://doi.org/10.1117/12.2042973

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available