NDLI: Discriminatively weighted multi-scale Local Binary Patterns: Applications in prostate cancer diagnosis on T2W MRI

Content Provider	IEEE Xplore Digital Library
Author	Haibo Wang Viswanath, S. Madabuhshi, A.
Copyright Year	2013
Abstract	In this paper, we present discriminatively weighted Local Binary Patterns (DWLBP), a new similarity metric to match Multi-scale LBP (MsLBP) in Hamming space. While MsLBP is widely used in image processing on account of its extremely fast bitwise operations on modern CPU, identifying a good metric that measures the dissimilarity of MsLBP remains an open problem. The Hamming score is typically computed at each individual scale and the scores across scales are summed up. This approach however often results in underestimating salient patterns. In this paper we seek to learn a vector obtained by optimally weighing the contribution of each individual scale when performing MsLBP based matching. Inspired by supervised learning, our methodology aims to learn the multi-scale, weight vector by minimizing the Hamming scores between positive class samples and jointly maximizing the scores between positive and negative class samples. This objective function leads to a convex formulation with equality and inequality constraints, which can then be solved via the interior-point optimization method. In this paper we evaluate the efficacy of the DWLBP scheme in detecting prostate cancer from T2w MRI and demonstrate that the approach statistically significantly outperforms MsLBP.
Sponsorship	IEEE
Starting Page	398
Ending Page	401
File Size	260274
Page Count	4
File Format	PDF
ISBN	9781467364560
ISSN	19457928
e-ISBN	9781467364553
DOI	10.1109/ISBI.2013.6556496
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Vectors Prostate cancer Measurement Heating Tuning multi-scale Prostate Cancer MRI Image Processing Local Binary Patterns
Content Type	Text
Resource Type	Article

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DISCRIMINATIVELY WEIGHTED MULTI-SCALE LOCAL BINARY PATTERNS: APPLICATIONS IN PROSTATE CANCER DIAGNOSIS ON T2W MRI

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