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Proceedings Paper

Limited angle breast ultrasound tomography with a priori information and artifact removal
Author(s): Rungroj Jintamethasawat; Yunhao Zhu; Oliver D. Kripfgans; Jie Yuan; Mitchell M. Goodsitt; Paul L. Carson
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Paper Abstract

In B-mode images from dual-sided ultrasound, it has been shown that by delineating structures suspected of being relatively homogeneous, one can enhance limited angle tomography to produce speed of sound images in the same view as X-ray Digital Breast Tomography (DBT). This could allow better breast cancer detection and discrimination, as well as improved registration of the ultrasound and X-ray images, because of the similarity of SOS and X-ray contrast in the breast. However, this speed of sound reconstruction method relies strongly on B-mode or other reflection mode segmentation. If that information is limited or incorrect, artifacts will appear in the reconstructed images. Therefore, the iterative speed of sound reconstruction algorithm has been modified in a manner of simultaneously utilizing the image segmentations and removing most artifacts. The first step of incorporating a priori information is solved by any nonlinearnonconvex optimization method while artifact removal is accomplished by employing the fast split Bregman method to perform total-variation (TV) regularization for image denoising. The proposed method was demonstrated in simplified simulations of our dual-sided ultrasound scanner. To speed these computations two opposed 40-element ultrasound linear arrays with 0.5 MHz center frequency were simulated for imaging objects in a uniform background. The proposed speed of sound reconstruction method worked well with both bent-ray and full-wave inversion methods. This is also the first demonstration of successful full-wave medical ultrasound tomography in the limited angle geometry. Presented results lend credibility to a possible translation of this method to clinical breast imaging.

Paper Details

Date Published: 13 March 2017
PDF: 12 pages
Proc. SPIE 10139, Medical Imaging 2017: Ultrasonic Imaging and Tomography, 101390N (13 March 2017); doi: 10.1117/12.2253911
Show Author Affiliations
Rungroj Jintamethasawat, Univ. of Michigan (United States)
Yunhao Zhu, Nanjing Univ. (China)
Oliver D. Kripfgans, Univ. of Michigan (United States)
Jie Yuan, Nanjing Univ. (China)
Mitchell M. Goodsitt, Univ. of Michigan (United States)
Paul L. Carson, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 10139:
Medical Imaging 2017: Ultrasonic Imaging and Tomography
Neb Duric; Brecht Heyde, Editor(s)

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