Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

Mandana Javanshir Moghaddam; Tao Tan; Nico Karssemeijer; Bram Platel

doi:10.1117/12.2043780

21 March 2014 Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

Mandana Javanshir Moghaddam, Tao Tan, Nico Karssemeijer, Bram Platel

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 903405 (2014) https://doi.org/10.1117/12.2043780
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

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.

Citation Download Citation

Mandana Javanshir Moghaddam, Tao Tan, Nico Karssemeijer, and Bram Platel "Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903405 (21 March 2014); https://doi.org/10.1117/12.2043780

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