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Proceedings Paper

Personalization of x-ray tube motion in digital breast tomosynthesis using virtual Defrise phantoms
Author(s): Raymond J. Acciavatti; Bruno Barufaldi; Trevor L. Vent; E. Paul Wileyto; Andrew D. A. Maidment
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Paper Abstract

In digital breast tomosynthesis (DBT), projection images are acquired as the x-ray tube rotates in the plane of the chest wall. We constructed a prototype next-generation tomosynthesis (NGT) system that has an additional component of tube motion in the perpendicular direction (i.e., posteroanterior motion). Our previous work demonstrated the advantages of the NGT system using the Defrise phantom. The reconstruction shows higher contrast and fewer blurring artifacts. To expand upon that work, this paper analyzes how image quality can be further improved by customizing the motion path of the x-ray tube based on the object being imaged. In simulations, phantoms are created with realistic 3D breast outlines based on an established model of the breast under compression. The phantoms are given an internal structure similar to a Defrise phantom. Two tissue types (fibroglandular and adipose) are arranged in a square-wave pattern. The reconstruction is analyzed as a binary classification task using thresholding to segment the two tissue types. At various thresholds, the classification of each voxel in the reconstruction is compared against the phantom, and receiver operating characteristic (ROC) curves are calculated. It is shown that the area under the ROC curve (AUC) is dependent on the x-ray tube trajectory. The trajectory that maximizes AUC differs between phantoms. In conclusion, this paper demonstrates that the acquisition geometry in DBT should be personalized to the object being imaged in order to optimize the image quality.

Paper Details

Date Published: 1 March 2019
PDF: 9 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109480B (1 March 2019); doi: 10.1117/12.2511780
Show Author Affiliations
Raymond J. Acciavatti, Univ. of Pennsylvania (United States)
Bruno Barufaldi, Univ. of Pennsylvania (United States)
Trevor L. Vent, Univ. of Pennsylvania (United States)
E. Paul Wileyto, Univ. of Pennsylvania (United States)
Andrew D. A. Maidment, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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