NDLI: Segmentation of anatomical branching structures based on texture features and graph cut

Content Provider	IEEE Xplore Digital Library
Author	Nuzhnaya, T. Erkang Cheng Haibin Ling Kontos, D. Bakic, P.R. Megalooikonomou, V.
Copyright Year	2011
Description	Author affiliation: Department of Radiology, University of Pennsylvania, 3400 Spruce St., Philadelphia, 19104, USA (Kontos, D.; Bakic, P.R.) \|\| Data Engineering Laboratory (DEnLab), Temple University, 1805 N. Broad St. Philadelphia, PA 19122, USA (Nuzhnaya, T.; Megalooikonomou, V.) \|\| Center for Information Science and Technology, Temple University, 1805 N. Broad St. Philadelphia, PA 19122, USA (Erkang Cheng; Haibin Ling)
Abstract	Segmentation of tree-like structure within medical imaging modalities, such as x-ray, MRI, ultrasound, etc., is an important step for analyzing branching patterns involved in many anatomic structures. However, images acquired using these different acquisition techniques frequently have features of poor contrast, blurring and noise, and therefore the segmentation result of traditional image segmentation methods may not be satisfactory. In this paper, we propose a framework for accurate segmentation of the ductal network in x-ray galactograms. Our approach is based on the graph cut algorithm and texture analysis to extract features of skewness, coarseness, contrast, energy and fractal dimension. The features are chosen to capture not only architectural variability of the enhanced ductal tree, but also spatial variations among pixels. The proposed approach was applied to a dataset of 20 galactographic images. We performed receiver operating characteristic (ROC) curve analysis to assess the accuracy. The area under the ROC curve observed was 0.76, indicating that our approach may potentially assist clinicians in the interpretation of breast images and facilitate the investigation of relationships among structure and texture of the branching patterns.
Starting Page	673
Ending Page	676
File Size	358141
Page Count	4
File Format	PDF
ISBN	9781424441273
ISSN	19457928
DOI	10.1109/ISBI.2011.5872496
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Pixel Breast Image edge detection X-ray imaging Fractals Biomedical imaging Texture features Branching Structure Breast Imaging Graph cut
Content Type	Text
Resource Type	Article

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