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Proceedings Paper

Feasibility study of breast tomosynthesis CAD system
Author(s): Anna Jerebko; Yuan Quan; Nicolas Merlet; Eli Ratner; Swatee Singh; Joseph Y. Lo; Arun Krishnan
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Paper Abstract

The purpose of this study was to investigate feasibility of computer-aided detection of masses and calcification clusters in breast tomosynthesis images and obtain reliable estimates of sensitivity and false positive rate on an independent test set. Automatic mass and calcification detection algorithms developed for film and digital mammography images were applied without any adaptation or retraining to tomosynthesis projection images. Test set contained 36 patients including 16 patients with 20 known malignant lesions, 4 of which were missed by the radiologists in conventional mammography images and found only in retrospect in tomosynthesis. Median filter was applied to tomosynthesis projection images. Detection algorithm yielded 80% sensitivity and 5.3 false positives per breast for calcification and mass detection algorithms combined. Out of 4 masses missed by radiologists in conventional mammography images, 2 were found by the mass detection algorithm in tomosynthesis images.

Paper Details

Date Published: 29 March 2007
PDF: 8 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 651414 (29 March 2007); doi: 10.1117/12.712729
Show Author Affiliations
Anna Jerebko, Siemens Med. (United States)
Yuan Quan, Siemens Med. (United States)
Nicolas Merlet, Siemens Med. (Israel)
Eli Ratner, Siemens Med. (Israel)
Swatee Singh, Duke Univ. (United States)
Joseph Y. Lo, Duke Univ. (United States)
Arun Krishnan, Siemens Med. (United States)


Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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