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Proceedings Paper

Image processing, radiological, and clinical information fusion in breast cancer detection
Author(s): Hilary Alto; Rangaraj M. Rangayyan; Basel Solaiman; J. E. Leo Desautels; J. H. MacGregor
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Paper Abstract

Screening mammography is the most efficient and cost-effective method available for detecting the signs of early breast cancer in asymptomatic women between the ages of 50 and 69. To improve the detection rate and reduce the number of unnecessary biopsies, many different computer-aided diagnosis techniques have been developed. Many of these techniques use image processing algorithms to automatically segment and classify the images. The decision-making process associated with the evaluation of mammograms is complex and incorporates multiple sources of information from standard medical knowledge and radiology to pathology. The use of this information combined with the results of image processing offers new challenges to the field of data and information fusion. In this paper, we describe the different information sources and their data as well as the framework that is needed to support this type of fusion. A database of breast cancer screening cases forms the basis of the resulting fusion model. The database and decision-level fusion techniques will facilitate unique and specialized approaches for efficient and sophisticated diagnosis of breast cancer.

Paper Details

Date Published: 6 March 2002
PDF: 11 pages
Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); doi: 10.1117/12.458377
Show Author Affiliations
Hilary Alto, Univ. of Calgary (Canada)
Rangaraj M. Rangayyan, Univ. of Calgary (Canada)
Basel Solaiman, Ecole Nationale Superieure des Telecommunications de Bretagne (France)
J. E. Leo Desautels, Univ. of Calgary and Alberta Cancer Board (Canada)
J. H. MacGregor, Univ. of Calgary and Foothills Medical Ctr. (Canada)

Published in SPIE Proceedings Vol. 4731:
Sensor Fusion: Architectures, Algorithms, and Applications VI
Belur V. Dasarathy, Editor(s)

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