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Proceedings Paper

Multiresolution Local Binary Pattern texture analysis for false positive reduction in computerized detection of breast masses on mammograms
Author(s): Jae Young Choi; Dae Hoe Kim; Seon Hyeong Choi; Yong Man Ro
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Paper Abstract

We investigated the feasibility of using multiresolution Local Binary Pattern (LBP) texture analysis to reduce falsepositive (FP) detection in a computerized mass detection framework. A new and novel approach for extracting LBP features is devised to differentiate masses and normal breast tissue on mammograms. In particular, to characterize the LBP texture patterns of the boundaries of masses, as well as to preserve the spatial structure pattern of the masses, two individual LBP texture patterns are then extracted from the core region and the ribbon region of pixels of the respective ROI regions, respectively. These two texture patterns are combined to produce the so-called multiresolution LBP feature of a given ROI. The proposed LBP texture analysis of the information in mass core region and its margin has clearly proven to be significant and is not sensitive to the precise location of the boundaries of masses. In this study, 89 mammograms were collected from the public MAIS database (DB). To perform a more realistic assessment of FP reduction process, the LBP texture analysis was applied directly to a total of 1,693 regions of interest (ROIs) automatically segmented by computer algorithm. Support Vector Machine (SVM) was applied for the classification of mass ROIs from ROIs containing normal tissue. Receiver Operating Characteristic (ROC) analysis was conducted to evaluate the classification accuracy and its improvement using multiresolution LBP features. With multiresolution LBP features, the classifier achieved an average area under the ROC curve, , z A of 0.956 during testing. In addition, the proposed LBP features outperform other state-of-the-arts features designed for false positive reduction.

Paper Details

Date Published: 23 February 2012
PDF: 7 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83152B (23 February 2012); doi: 10.1117/12.911137
Show Author Affiliations
Jae Young Choi, Korea Advanced Institute of Science and Technology (Korea, Democratic Peoples Republic of)
Dae Hoe Kim, Korea Advanced Institute of Science and Technology (Korea, Democratic Peoples Republic of)
Seon Hyeong Choi, Sungkyunkwan Univ. (Korea, Democratic Peoples Republic of)
Yong Man Ro, Korea Advanced Institute of Science and Technology (Korea, Democratic Peoples Republic of)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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