Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis

K. P. Lin; H. D. Lin; C. L. Yu; L. C. Wu; R. S. Liu

doi:10.1109/IEMBS.2000.900784

Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis

K. P. Lin^*, H. D. Lin, C. L. Yu, L. C. Wu, R. S. Liu

^*此作品的通信作者

生物醫學影像暨放射科學系

研究成果: Conference article › 同行評審

摘要

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 achieved. To improve the quality problem of PET image, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subbands of the PET image.

原文	English
頁（從 - 到）	494-497
頁數	4
期刊	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
卷	1
DOIs	https://doi.org/10.1109/IEMBS.2000.900784
出版狀態	Published - 7月 2000
事件	22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States 持續時間: 23 7月 2000 → 28 7月 2000

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10.1109/IEMBS.2000.900784

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@article{e35b3a3ebe124245890705fb4f45a731,

title = "Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis",

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 achieved. To improve the quality problem of PET image, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subbands of the PET image.",

keywords = "Positron emission tomographic (PET), Wavelet denoising technique",

author = "Lin, {K. P.} and Lin, {H. D.} and Yu, {C. L.} and Wu, {L. C.} and Liu, {R. S.}",

year = "2000",

month = jul,

doi = "10.1109/IEMBS.2000.900784",

language = "English",

volume = "1",

pages = "494--497",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 23-07-2000 Through 28-07-2000",

}

TY - JOUR

T1 - Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis

AU - Lin, K. P.

AU - Lin, H. D.

AU - Yu, C. L.

AU - Wu, L. C.

AU - Liu, R. S.

PY - 2000/7

Y1 - 2000/7

N2 - 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 achieved. To improve the quality problem of PET image, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subbands of the PET image.

AB - 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 achieved. To improve the quality problem of PET image, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subbands of the PET image.

KW - Positron emission tomographic (PET)

KW - Wavelet denoising technique

UR - http://www.scopus.com/inward/record.url?scp=0034442608&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2000.900784

DO - 10.1109/IEMBS.2000.900784

M3 - Conference article

AN - SCOPUS:0034442608

SN - 0589-1019

VL - 1

SP - 494

EP - 497

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 23 July 2000 through 28 July 2000

ER -

Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis

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