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

Volume

1

fYear

2000

fDate

2000

Firstpage

494

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1094-687X

Print_ISBN

0-7803-6465-1

Type

conf

DOI

10.1109/IEMBS.2000.900784

Filename

900784