Computer-Aided Detection of Lesions in Digital Breast Tomosynthesis Images

Prinzen M, Wagner F, Nowack S, Schulz-Wendtland R, Paulus D, Wittenberg T (2014)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2014

Journal

Informatik aktuell Gesellschaft für Informatik (GI)

Publisher: Springer-Verlag

Edited Volumes: Informatik aktuell

Series: Informatik Aktuell

City/Town: Heidelberg

Pages Range: 162-167

Conference Proceedings Title: Bildverarbeitung für die Medizin 2014

Event location: Aachen

ISBN: 9783642541100

URI: https://link.springer.com/chapter/10.1007/978-3-642-54111-7_33

DOI: 10.1007/978-3-642-54111-7_33

Abstract

The most common cancer among women in the western world is breast cancer. Early detection of lesions greatly influences the progress and success of its treatment. Digital breast tomosynthesis (DBT) is a new imaging technique that facilitates a three-dimensional reconstruction of the breast. DBT reduces superimposition of breast tissues and provides better insight into the breast compared to the common digital mammography. In order to assist radiologists with the examination and assessment of the large amount of DBT data, a computer aided detection (CADe) of focal lesions can be an essential tool, leading to increased sensitivity and specificity. We present and compare two different approaches for a fully automated detection of lesions in DBT data using voxel-wise classification, one being the state of the art and the other one an enhancement. Multiple difference of Gaussians detect lesions based on their common higher intensity and contrast in relation to surrounding tissue. A gradient orientation analysis detects round and spiculated lesions, even when they are weak in contrast and intensity. By combining these features and using a support vector machine, a classification performance of 88% can be achieved.

Authors with CRIS profile

Florian Wagner Chair of Visual Computing (LGDV) Thomas Wittenberg Technische Fakultät

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE)

How to cite

APA:

Prinzen, M., Wagner, F., Nowack, S., Schulz-Wendtland, R., Paulus, D., & Wittenberg, T. (2014). Computer-Aided Detection of Lesions in Digital Breast Tomosynthesis Images. In Thomas Martin DesernoHeinz HandelsHans-Peter MeinzerThomas Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2014 (pp. 162-167). Aachen: Heidelberg: Springer-Verlag.

MLA:

Prinzen, Martin, et al. "Computer-Aided Detection of Lesions in Digital Breast Tomosynthesis Images." Proceedings of the Bildverarbeitung für die Medizin, Aachen Ed. Thomas Martin DesernoHeinz HandelsHans-Peter MeinzerThomas Tolxdorff, Heidelberg: Springer-Verlag, 2014. 162-167.

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