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Proceedings Paper

Segmentation methods for breast vasculature in dual-energy contrast-enhanced digital breast tomosynthesis
Author(s): Kristen C. Lau; Hyo Min Lee; Tanushriya Singh; Andrew D. A. Maidment
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Paper Abstract

Dual-energy contrast-enhanced digital breast tomosynthesis (DE CE-DBT) uses an iodinated contrast agent to image the three-dimensional breast vasculature. The University of Pennsylvania has an ongoing DE CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 post-contrast). DE images are obtained by a weighted logarithmic subtraction of the high-energy (HE) and low-energy (LE) image pairs. Temporal subtraction of the post-contrast DE images from the pre-contrast DE image is performed to analyze iodine uptake. Our previous work investigated image registration methods to correct for patient motion, enhancing the evaluation of vascular kinetics. In this project we investigate a segmentation algorithm which identifies blood vessels in the breast from our temporal DE subtraction images. Anisotropic diffusion filtering, Gabor filtering, and morphological filtering are used for the enhancement of vessel features. Vessel labeling methods are then used to distinguish vessel and background features successfully. Statistical and clinical evaluations of segmentation accuracy in DE-CBT images are ongoing.

Paper Details

Date Published: 23 April 2015
PDF: 12 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 941227 (23 April 2015); doi: 10.1117/12.2081031
Show Author Affiliations
Kristen C. Lau, The Univ. of Pennsylvania (United States)
Hyo Min Lee, The Univ. of Pennsylvania (United States)
Tanushriya Singh, The Univ. of Pennsylvania (United States)
Andrew D. A. Maidment, The Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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