Wavelet based de-noising methods for local SPECT reconstruction

Jun Hai Wen; Li Wang; Jing Yang; Yun Bin Chen; Zheng Rong Liang

Wavelet based de-noising methods for local SPECT reconstruction

Jun Hai Wen
, Li Wang
, Jing Yang
, Yun Bin Chen
, Zheng Rong Liang

Radiology

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Local reconstruction algorithm has been proposed to reduce the reconstructing time in the single photon emission computer tomography (SPECT). To improve the image quality, it is necessary to de-noise the projection image before reconstruction. Revised biva-shrinkage de-nosing based on wavelet transformation, which has a property of reserving detail information, is used to pre-treat the image. The mean square error (MSE) is adopted to evaluate the de-noising image of local reconstruction. The results show that wavelet based de-noising method is effective in local reconstruction algorithm.

Original language	English
Pages (from-to)	956-959
Number of pages	4
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	30
Issue number	8
State	Published - Aug 2010

Keywords

Biva-shrinkage
Local reconstruction
Mean square error(MSE)
Single photon emission computer tomography(SPECT)
Wavelet transformation

Cite this

@article{38c7bc45aaf74c7d88c4ab109e17b0bd,

title = "Wavelet based de-noising methods for local SPECT reconstruction",

abstract = "Local reconstruction algorithm has been proposed to reduce the reconstructing time in the single photon emission computer tomography (SPECT). To improve the image quality, it is necessary to de-noise the projection image before reconstruction. Revised biva-shrinkage de-nosing based on wavelet transformation, which has a property of reserving detail information, is used to pre-treat the image. The mean square error (MSE) is adopted to evaluate the de-noising image of local reconstruction. The results show that wavelet based de-noising method is effective in local reconstruction algorithm.",

keywords = "Biva-shrinkage, Local reconstruction, Mean square error(MSE), Single photon emission computer tomography(SPECT), Wavelet transformation",

author = "Wen, \{Jun Hai\} and Li Wang and Jing Yang and Chen, \{Yun Bin\} and Liang, \{Zheng Rong\}",

year = "2010",

month = aug,

language = "English",

volume = "30",

pages = "956--959",

journal = "Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology",

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T1 - Wavelet based de-noising methods for local SPECT reconstruction

AU - Wen, Jun Hai

AU - Wang, Li

AU - Yang, Jing

AU - Chen, Yun Bin

AU - Liang, Zheng Rong

PY - 2010/8

Y1 - 2010/8

N2 - Local reconstruction algorithm has been proposed to reduce the reconstructing time in the single photon emission computer tomography (SPECT). To improve the image quality, it is necessary to de-noise the projection image before reconstruction. Revised biva-shrinkage de-nosing based on wavelet transformation, which has a property of reserving detail information, is used to pre-treat the image. The mean square error (MSE) is adopted to evaluate the de-noising image of local reconstruction. The results show that wavelet based de-noising method is effective in local reconstruction algorithm.

AB - Local reconstruction algorithm has been proposed to reduce the reconstructing time in the single photon emission computer tomography (SPECT). To improve the image quality, it is necessary to de-noise the projection image before reconstruction. Revised biva-shrinkage de-nosing based on wavelet transformation, which has a property of reserving detail information, is used to pre-treat the image. The mean square error (MSE) is adopted to evaluate the de-noising image of local reconstruction. The results show that wavelet based de-noising method is effective in local reconstruction algorithm.

KW - Biva-shrinkage

KW - Local reconstruction

KW - Mean square error(MSE)

KW - Single photon emission computer tomography(SPECT)

KW - Wavelet transformation

UR - https://www.scopus.com/pages/publications/77958082018

M3 - Article

AN - SCOPUS:77958082018

SN - 1001-0645

VL - 30

SP - 956

EP - 959

JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 8

ER -

Wavelet based de-noising methods for local SPECT reconstruction

Abstract

Keywords

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