Anisotropic filtering technique for PET image edge extraction
Han-Yuan Wang, Kang‐Ping Lin, Hong-Dun Lin, Chin-Lung Yu, Liang-Chih Wu, Ren-Shyan Liu · 2002
Since the positron emission tomographic (PET) image shows the abnormal activity of brain by the different parts of the brain respond to different stimuli and the patient's response to noise, illumination, change in mental concentration, and other activity, the functional PET image data is much helpful for clinical diagnosis. However, the PET image is also a high noise image that the quality of the PET image and the diagnosis accuracy is effected by the noise. To solve this problem, a novel nonlinear anisotropic filtering technique was applied. Because it will make the blurring of object boundaries and the suppression of fine structural details by using traditional filter, the method is 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.