Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model

Myungeun Lee; Jong Hyo Kim

doi:10.1117/12.911181

14 February 2012 Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model

Myungeun Lee, Jong Hyo Kim

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83142P (2012) https://doi.org/10.1117/12.911181
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Recently, breast MR images have been used in wider clinical area including diagnosis, treatment planning, and treatment response evaluation, which requests quantitative analysis and breast tissue segmentation. Although several methods have been proposed for segmenting MR images, segmenting out breast tissues robustly from surrounding structures in a wide range of anatomical diversity still remains challenging. Therefore, in this paper, we propose a practical and general-purpose approach for segmenting the pectoral muscle boundary based on the structure tensor and deformable model. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle robustly in diverse patient cases. In addition, the proposed method will allow the application of the quantification research for various breast images.

Citation Download Citation

Myungeun Lee and Jong Hyo Kim "Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83142P (14 February 2012); https://doi.org/10.1117/12.911181

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