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Proceedings Paper

Non-rigid ultrasound image registration using generalized relaxation labeling process
Author(s): Jong-Ha Lee; Yeong Kyeong Seong; MoonHo Park; Kyoung-Gu Woo; Jeonghun Ku; Hee-Jun Park
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Paper Abstract

This research proposes a novel non-rigid registration method for ultrasound images. The most predominant anatomical features in medical images are tissue boundaries, which appear as edges. In ultrasound images, however, other features can be identified as well due to the specular reflections that appear as bright lines superimposed on the ideal edge location. In this work, an image’s local phase information (via the frequency domain) is used to find the ideal edge location. The generalized relaxation labeling process is then formulated to align the feature points extracted from the ideal edge location. In this work, the original relaxation labeling method was generalized by taking n compatibility coefficient values to improve non-rigid registration performance. This contextual information combined with a relaxation labeling process is used to search for a correspondence. Then the transformation is calculated by the thin plate spline (TPS) model. These two processes are iterated until the optimal correspondence and transformation are found. We have tested our proposed method and the state-of-the-art algorithms with synthetic data and bladder ultrasound images of in vivo human subjects. Experiments show that the proposed method improves registration performance significantly, as compared to other state-of-the-art non-rigid registration algorithms.

Paper Details

Date Published: 6 March 2013
PDF: 6 pages
Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 86610I (6 March 2013); doi: 10.1117/12.2003233
Show Author Affiliations
Jong-Ha Lee, Keimyung Univ. (Korea, Republic of)
Yeong Kyeong Seong, Samsung Advanced Institute of Technology (Korea, Republic of)
MoonHo Park, Samsung Advanced Institute of Technology (Korea, Republic of)
Kyoung-Gu Woo, Samsung Advanced Institute of Technology (Korea, Republic of)
Jeonghun Ku, Keimyung Univ. (Korea, Republic of)
Hee-Jun Park, Keimyung Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 8661:
Image Processing: Machine Vision Applications VI
Philip R. Bingham; Edmund Y. Lam, Editor(s)

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