By Topic

Geometric Active Model for Lesion Segmentation on Breast Ultrasound Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Myungeun Lee ; Dept. of Comput. Sci., Chonnam Nat. Univ., Gwangju, South Korea ; Yanjuan Chen ; Soohyung Kim ; Kwanggi Kim

Ultrasound image segmentation is a difficult task due to the low contrast, blurry and signal/noise ratio. Hence, in this paper, we propose a segmentation method for ultrasound image using the level set method. In particular, the level set method utilizes a new derived speed function to improve the segmentation performance. This speed function provides a general form that incorporates an alignment term as a part of the driving force for the proper edge direction of active contour, a probability term derived from the region partition scheme, and a smoothing term for regularization. Next, we test the accuracy and robustness of the proposed method for mass segmentation of various breast ultrasound images. The experimental results show that our method is relatively more excellent on effectiveness and performance than traditional approaches. Consequently, the results show the potential of our methodology to extract breast mass which could help to reduce false positives in subsequent computer aided lesion segmentation.

Published in:

Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on

Date of Conference:

Aug. 31 2011-Sept. 2 2011