Automated breast-region segmentation in the axial breast MR images.
OBJECTIVE
The purpose of this study was to develop a robust breast-region segmentation method independent from the visible contrast between the breast region and surrounding chest wall and skin.


METHODS
A fully-automated method for segmentation of the breast region in the axial MR images is presented relying on the edge map (EM) obtained by applying a tunable Gabor filter which sets its parameters according to the local MR image characteristics to detect non-visible transitions between different tissues having a similar MRI signal intensity. The method applies the shortest-path search technique by incorporating a novel cost function using the EM information within the border-search area obtained based on the border information from the adjacent slice. It is validated on 52 MRI scans covering the full American College of Radiology Breast Imaging-Reporting and Data System (BI-RADS) breast-density range.


RESULTS
The obtained results indicate that the method is robust and applicable for the challenging cases where a part of the fibroglandular tissue is connected to the chest wall and/or skin with no visible contrast, i.e. no fat presence, between them compared to the literature methods proposed for the axial MR images. The overall agreement between automatically- and manually-obtained breast-region segmentations is 96.1% in terms of the Dice Similarity Coefficient, and for the breast-chest wall and breast-skin border delineations it is 1.9mm and 1.2mm, respectively, in terms of the Mean-Deviation Distance.


CONCLUSIONS
The accuracy, robustness and applicability for the challenging cases of the proposed method show its potential to be incorporated into computer-aided analysis systems to support physicians in their decision making.
Faculty for Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia. Electronic address: jana.milenkovic@fe.uni-lj.si.
Jana
J
Milenković
Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia.
Olga
O
Chambers
Institute of Oncology, Zaloška 2, 1000 Ljubljana, Slovenia.
Maja
M
Marolt Mušič
Faculty for Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia.
Jurij Franc
JF
Tasič
D001940:Breast; D003658:Decision Making, Computer-Assisted; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008327:Mammography / Q000379:methods*
Breast MRI; Breast-region segmentation; Cost function; Shortest-path search; Tunable Gabor filter