Fully automated nipple detection in 3D breast ultrasound images

Wang L, Böhler T, Zöhrer F, Georgii J, Rauh C, Fasching P, Brehm B, Schulz-Wendtland R, Beckmann M, Uder M, Hahn HK (2014)

Publication Type: Conference contribution

Publication year: 2014

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 8539 LNCS

Pages Range: 64-71

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: JPN

ISBN: 9783319078861

DOI: 10.1007/978-3-319-07887-8_10

Abstract

Nipple position provides useful diagnostic informations in reading automated 3D breast ultrasound (ABUS) images. The identification of nipples is required to localize and determine the quadrants of breast lesions. Additionally, the nipple position serves as an effective landmark to register an ABUS image to other imaging modalities, such as digital mammography, breast magnet resonance imaging (MRI), or tomosynthesis. Nevertheless, the presence of speckle noise induced by interference waves and variant imaging directions in ultrasonography poses challenges to the task. In this work, we propose a fast and automated algorithm to detect nipples in 3D breast ultrasound images. The method fully takes advantages of the consistent characteristics of ultrasonographic signals observed at nipples and employs a multi-scale Laplacian-based blob detector to eventually identify nipple positions. The accuracy of the proposed method was tested on 113 ABUS images, resulting in a distance error of 6.6±8.9 mm (mean ±std). © 2014 Springer International Publishing.

Authors with CRIS profile

Peter Fasching Professur für Translationale Frauenheilkunde und Geburtshilfe Barbara Brehm Institute of Radiology Matthias Beckmann Lehrstuhl für Geburtshilfe und Frauenheilkunde Michael Uder Lehrstuhl für Diagnostische Radiologie

Involved external institutions

Fraunhofer-Institut für Bildgestützte Medizin (MEVIS) DE Germany (DE)

How to cite

APA:

Wang, L., Böhler, T., Zöhrer, F., Georgii, J., Rauh, C., Fasching, P.,... Hahn, H.K. (2014). Fully automated nipple detection in 3D breast ultrasound images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 64-71). JPN: Springer Verlag.

MLA:

Wang, Lei, et al. "Fully automated nipple detection in 3D breast ultrasound images." Proceedings of the 12th International Workshop on Breast Imaging, IWDM 2014, JPN Springer Verlag, 2014. 64-71.

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