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Proceedings Paper

Role of computer aided detection (CAD) integration: case study with meniscal and articular cartilage CAD applications
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Paper Abstract

Knee-related injuries involving the meniscal or articular cartilage are common and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and experience, confidence in detection of meniscal tears and articular cartilage abnormalities can be quite high. However, for radiologists without musculoskeletal training, diagnosis of such abnormalities can be challenging. In this paper, the potential of improving diagnosis through integration of computer-aided detection (CAD) algorithms for automatic detection of meniscal tears and articular cartilage injuries of the knees is studied. An integrated approach in which the results of algorithms evaluating either meniscal tears or articular cartilage injuries provide feedback to each other is believed to improve the diagnostic accuracy of the individual CAD algorithms due to the known association between abnormalities in these distinct anatomic structures. The correlation between meniscal tears and articular cartilage injuries is exploited to improve the final diagnostic results of the individual algorithms. Preliminary results from the integrated application are encouraging and more comprehensive tests are being planned.

Paper Details

Date Published: 13 March 2008
PDF: 7 pages
Proc. SPIE 6919, Medical Imaging 2008: PACS and Imaging Informatics, 69190J (13 March 2008); doi: 10.1117/12.779304
Show Author Affiliations
Nabile Safdar, Univ. of Maryland School of Medicine (United States)
Bharath Ramakrishna, Univ. of Maryland Baltimore County (United States)
Ganesh Saiprasad, Univ. of Maryland Baltimore County (United States)
Khan Siddiqui, VA Maryland Health Care System (United States)
Eliot Siegel, Univ. of Maryland School of Medicine (United States)
VA Maryland Health Care System (United States)


Published in SPIE Proceedings Vol. 6919:
Medical Imaging 2008: PACS and Imaging Informatics
Katherine P. Andriole; Khan M. Siddiqui, Editor(s)

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