Paper
17 March 2008 Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method
Author Affiliations +
Abstract
The goal of this study was to develop an automated method to segment breast masses on dynamic contrast-enhanced (DCE) magnetic resonance (MR) scans that were performed to monitor breast cancer response to neoadjuvant chemotherapy. A radiologist experienced in interpreting breast MR scans defined the mass using a cuboid volume of interest (VOI). Our method then used the K-means clustering algorithm followed by morphological operations for initial mass segmentation on the VOI. The initial segmentation was then refined by a three-dimensional level set (LS) method. The velocity field of the LS method was formulated in terms of the mean curvature which guaranteed the smoothness of the surface and the Sobel edge information which attracted the zero LS to the desired mass margin. We also designed a method to reduce segmentation leak by adapting a region growing technique. Our method was evaluated on twenty DCE-MR scans of ten patients who underwent neoadjuvant chemotherapy. Each patient had pre- and post-chemotherapy DCE-MR scans on a 1.5 Tesla magnet. Computer segmentation was applied to coronal T1-weighted images. The in-plane pixel size ranged from 0.546 to 0.703 mm and the slice thickness ranged from 2.5 to 4.0 mm. The flip angle was 15 degrees, repetition time ranged from 5.98 to 6.7 ms, and echo time ranged from 1.2 to 1.3 ms. The computer segmentation results were compared to the radiologist's manual segmentation in terms of the overlap measure defined as the ratio of the intersection of the computer and the radiologist's segmentations to the radiologist's segmentation. Pre- and post-chemotherapy masses had overlap measures of 0.81±0.11 (mean±s.d.) and 0.70±0.21, respectively.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiazheng Shi, Berkman Sahiner, Heang-Ping Chan, Chintana Paramagul, Lubomir M. Hadjiiski, Mark Helvie, Yi-Ta Wu, Jun Ge, Yiheng Zhang, Chuan Zhou, and Jun Wei "Breast mass segmentation on dynamic contrast-enhanced magnetic resonance scans using the level set method", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69152A (17 March 2008); https://doi.org/10.1117/12.771390
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Breast

3D image processing

Magnetic resonance imaging

Magnetism

3D acquisition

Breast cancer

Back to Top