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Proceedings Paper

Abnormal breast tissue imaging based on multi-energy x-ray
Author(s): Dong-Goo Kang; Seok-Min Han; Younghun Sung; SeongDeok Lee
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Paper Abstract

The dual or multi-energy x-ray technique facilitates to generate tissue-selective images, by exploiting tissue-specific energy dependence of x-ray attenuation. An abnormal breast is considered to be a mixture of adipose, glandular, and abnormal tissues, but three tissues cannot be selectively decomposed because the total attenuation of a tissue is represented by only two attenuation basis functions at diagnostic energy range. This paper presents a novel method to selectively represent abnormal breast tissue, using polyenergetic multi-energy x-ray. We show that an abnormal tissue can be revealed from the total thickness map, which is virtually constructed by assuming a healthy and compressed breast. Specifically, regression analysis is first performed using the multi-energy images of the prepared calibration phantom that consists of two basis materials. Total thickness map is then constructed by linearly combining thickness maps of basis materials, where the optimal weights for combination are determined so that the uniformity of total breast thickness is maximized. It is noted that the proposed method does not need accurate attenuation coefficients of breast tissues. Simulation results show that the proposed method dramatically improves the detectability of mass that is obscured by normal structures.

Paper Details

Date Published: 16 March 2011
PDF: 8 pages
Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 796156 (16 March 2011); doi: 10.1117/12.877916
Show Author Affiliations
Dong-Goo Kang, Samsung Electronics Co., Ltd. (Korea, Republic of)
Seok-Min Han, Samsung Electronics Co., Ltd. (Korea, Republic of)
Younghun Sung, Samsung Electronics Co., Ltd. (Korea, Republic of)
SeongDeok Lee, Samsung Electronics Co., Ltd. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7961:
Medical Imaging 2011: Physics of Medical Imaging
Norbert J. Pelc; Ehsan Samei; Robert M. Nishikawa, Editor(s)

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