Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.

Tao Tan¹, Albert Gubern-Mérida¹, Cristina Borelli², Rashindra Manniesing¹, Jan van Zelst¹, Lei Wang³, Wei Zhang⁴, Bram Platel¹, Ritse M Mann¹, Nico Karssemeijer¹

¹Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.

²Department of Radiological Sciences, Catholic University, Policlinic A. Gemelli, Rome 00168, Italy.

³Fraunhofer Mevis, Bremen 28359, Germany.

⁴QView Medical, Inc., Los Altos, California 94022.

PubMed DOI

Abstract

PURPOSE: Automated 3D breast ultrasound (ABUS) has been proposed as a complementary screening modality to mammography for early detection of breast cancers. To facilitate the interpretation of ABUS images, automated diagnosis and detection techniques are being developed, in which malignant lesion segmentation plays an important role. However, automated segmentation of cancer in ABUS is challenging…

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