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Proceedings Paper

Biased anisotropic diffusion method for PET image segmentation
Author(s): Hong-Dun Lin; Han-Yuan Wang; Yu-Chang Hu; Kang-Ping Lin; Chin-Lung Yu; Liang-Chi Wu; Ren-Shyan Liu
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Paper Abstract

In the context of functional positron emission tomographic (PET) images analysis, the segmentation method can not only entails the separation of the image into regions of similar attribute but also presents clearer understanding about the features embedded in the original image to improve the quantitative analysis. However, for completely recording, clinical instruments often collect subject signal as well as signals from background environment, which are regarded as noises of various levels. High noise often makes the original PET image unrecognizable and difficult to analyze. Thus, manual or semiautomatic methods have been utilized to overcome the difficulty of high noise image segmentation. Furthermore, the success of image segmentation is one of the important key factors in the accompanying automated system, and there has been no general segmentation method that can be applied to the high noise PET images of different feature characteristics. However, the PET image is high noisy causing by the imaging procedure, and the image quality of PET image is affected inherently. To improve this issue, a novel nonlinear anisotropic diffusion technique based on the diffusion theorem with multi-scale and edge detection scheme to inhibit the noise level and hold the boundary characteristics of the high noise PET image was provided in this paper.

Paper Details

Date Published: 21 May 2001
PDF: 8 pages
Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); doi: 10.1117/12.428167
Show Author Affiliations
Hong-Dun Lin, Chung-Yuan Christian Univ. (Taiwan)
Han-Yuan Wang, Chung-Yuan Christian Univ. (Taiwan)
Yu-Chang Hu, Chung-Yuan Christian Univ. (Taiwan)
Kang-Ping Lin, Chung-Yuan Christian Univ. (Taiwan)
Chin-Lung Yu, Taipei Veterans General Hospital (Taiwan)
Liang-Chi Wu, Taipei Veterans General Hospital (Taiwan)
Ren-Shyan Liu, Taipei Veterans General Hospital (Taiwan)

Published in SPIE Proceedings Vol. 4321:
Medical Imaging 2001: Physiology and Function from Multidimensional Images
Chin-Tu Chen; Anne V. Clough, Editor(s)

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