Title :
Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis
Author :
Lin, Kang-Ping ; Lin, Hong-Dun ; Yu, Chin-Lung ; Wu, Liang-Chih ; Liu, Ren-Shyan
Author_Institution :
Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung Li, Taiwan
Abstract :
In generally, the dynamic positron emission tomographic image (PET) that imaging with FDOPA plays as a powerful functional image tool to clinical diagnosis for the tissue disorders of Parkinson´s disease. However, high noise is always shown in dynamic FDOPA, so that the accuracy of the pixel-based parametric image is not easy to achieve. To improve the quality problem of PET images, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subband of the PET image
Keywords :
diseases; medical image processing; noise; positron emission tomography; statistical analysis; wavelet transforms; PET image quality; dynamic FDOPA-PET images analysis; image accuracy; medical diagnostic imaging; nuclear medicine; statistical features; statistical-based wavelet denoising technique; subband denoising technique; subbands; Frequency; Image analysis; Low pass filters; Noise level; Noise reduction; Parkinson´s disease; Positron emission tomography; Radioactive decay; Wavelet analysis; Wavelet coefficients;
Conference_Titel :
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-6465-1
DOI :
10.1109/IEMBS.2000.900784
