NDLI: Computer-aided diagnosis of mammographic masses using vocabulary tree-based image retrieval

Content Provider	IEEE Xplore Digital Library
Author	Menglin Jiang Shaoting Zhang Jingjing Liu Tian Shen Metaxas, D.N.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Rutgers Univ., Piscataway, NJ, USA (Menglin Jiang; Jingjing Liu; Metaxas, D.N.) \|\| Hwatech Med. Inf.-Tech Co., Xi'An, China (Tian Shen) \|\| Dept. of Comput. Sci., UNC Charlotte, Charlotte, NC, USA (Shaoting Zhang)
Abstract	Computer-aided diagnosis of masses in mammograms is important to the prevention of breast cancer. Many approaches tackle this problem through content-based image retrieval (CBIR) techniques. However, most of them fall short of scalability in the retrieval stage, and their diagnostic accuracy is therefore restricted. To overcome this drawback, we propose a scalable method for retrieval and diagnosis of mam-mographic masses. Specifically, for a query mammographic region of interest (ROI), SIFT descriptors are extracted and searched in a vocabulary tree, which stores all the quantized descriptors of previously diagnosed mammographic ROIs. In addition, to fully exert the discriminative power of SIFT descriptors, contextual information in the vocabulary tree is employed to refine the weights of tree nodes. The retrieved ROIs are then used to determine whether the query ROI contains a mass. This method has excellent scalability due to the low spatial-temporal cost of vocabulary tree. Retrieval precision and diagnostic accuracy are evaluated on 5005 ROIs extracted from the digital database for screening mammography (DDSM), which demonstrate the efficacy of our approach.
Starting Page	1123
Ending Page	1126
File Size	1204229
Page Count	4
File Format	PDF
ISBN	9781467319614
DOI	10.1109/ISBI.2014.6868072
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-04-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vocabulary Accuracy Image retrieval Design automation Computer aided diagnosis Breast cancer content-based image retrieval (CBIR) Mammographic masses computer-aided diagnosis (CAD)
Content Type	Text
Resource Type	Article

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