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Proceedings Paper

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)
Author(s): Mandana Javanshir Moghaddam; Tao Tan; Nico Karssemeijer; Bram Platel
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Paper Abstract

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

Paper Details

Date Published: 21 March 2014
PDF: 6 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903405 (21 March 2014); doi: 10.1117/12.2043780
Show Author Affiliations
Mandana Javanshir Moghaddam, Radboud Univ. Nijmegen Medical Ctr. (Netherlands)
Tao Tan, Radboud Univ. Nijmegen Medical Ctr. (Netherlands)
Nico Karssemeijer, Radboud Univ. Nijmegen Medical Ctr. (Netherlands)
Bram Platel, Radboud Univ. Nijmegen Medical Ctr. (Netherlands)


Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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