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Mammogram image retrieval via sparse representation

Siyahjani, F ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1109/MECBME.2011.5752065
  3. Publisher: 2011
  4. Abstract:
  5. In recent years there has been a great effort to enhance the computer-aided diagnosis systems, since proven similar pathologies, in the past, plays an important role in diagnosis of the current cases, content based medical image retrieval has been emerged. In this work we have designed a decision making machine in which utilizes sparse representation technique to preserve semantic category relevance among the retrieved images and the query image, this machine comprises optimized wavelets (adapted using lifting scheme) to extract appropriate visual features in order to grasp visual content of the images, afterwards by using some classical methods, Raw data vectors become applicable for sparse representation. We implemented our algorithm on the DDSM database which consists of 2500 studies and their annotations provided by specialists
  6. Keywords:
  7. Classical methods ; Computer-aided diagnosis system ; Content based medical image retrieval ; Data vectors ; Decision making machines ; Lifting schemes ; Query images ; Retrieved images ; Semantic category ; Sparse representation ; Visual content ; Visual feature ; Computer aided diagnosis ; Decision making ; Image retrieval ; Medical imaging ; Medicine ; Semantics ; Search engines
  8. Source: 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, Sharjah, 21 February 2011 through 24 February 2011 ; 2011 , Pages 63-66 ; 9781424470006 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5752065