A rapid medical image noise variance estimation method

F. F. Ting; K. S. Sim; E. K. Wong

doi:10.1109/ICORAS.2016.7872628

A rapid medical image noise variance estimation method

F. F. Ting, K. S. Sim, E. K. Wong

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

5 Citations (Scopus)

Abstract

Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the image through GWLC. A performance comparison between our proposed method and referred method are carried out. GWLC outperforms other related methods.

Original language	English
Title of host publication	Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509062058
DOIs	https://doi.org/10.1109/ICORAS.2016.7872628
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Robotics, Automation and Sciences 2016 - Melaka, Malaysia Duration: 5 Nov 2016 → 6 Nov 2016 https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding (Proceedings)

Conference

Conference	International Conference on Robotics, Automation and Sciences 2016
Abbreviated title	ICORAS 2016
Country	Malaysia
City	Melaka
Period	5/11/16 → 6/11/16
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding (Proceedings)

Keywords

Biomedical Imaging
Computed Tomography
Image Processing
Medical Imaging
Noise Estimation

Access to Document

10.1109/ICORAS.2016.7872628

Link to publication in Scopus

Cite this

@inproceedings{d73d8b7e82a94576b9b840e1233acd7f,

title = "A rapid medical image noise variance estimation method",

abstract = "Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the image through GWLC. A performance comparison between our proposed method and referred method are carried out. GWLC outperforms other related methods.",

keywords = "Biomedical Imaging, Computed Tomography, Image Processing, Medical Imaging, Noise Estimation",

author = "Ting, {F. F.} and Sim, {K. S.} and Wong, {E. K.}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; International Conference on Robotics, Automation and Sciences 2016, ICORAS 2016 ; Conference date: 05-11-2016 Through 06-11-2016",

year = "2016",

doi = "10.1109/ICORAS.2016.7872628",

language = "English",

booktitle = "Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/7864798/proceeding",

}

Ting, FF, Sim, KS & Wong, EK 2016, A rapid medical image noise variance estimation method. in Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016. IEEE, Institute of Electrical and Electronics Engineers, International Conference on Robotics, Automation and Sciences 2016, Melaka, Malaysia, 5/11/16. https://doi.org/10.1109/ICORAS.2016.7872628

TY - GEN

T1 - A rapid medical image noise variance estimation method

AU - Ting, F. F.

AU - Sim, K. S.

AU - Wong, E. K.

PY - 2016

Y1 - 2016

N2 - Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the image through GWLC. A performance comparison between our proposed method and referred method are carried out. GWLC outperforms other related methods.

AB - Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the image through GWLC. A performance comparison between our proposed method and referred method are carried out. GWLC outperforms other related methods.

KW - Biomedical Imaging

KW - Computed Tomography

KW - Image Processing

KW - Medical Imaging

KW - Noise Estimation

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U2 - 10.1109/ICORAS.2016.7872628

DO - 10.1109/ICORAS.2016.7872628

M3 - Conference Paper

AN - SCOPUS:85016951593

BT - Proceedings of 2016 International Conference on Robotics, Automation and Sciences, ICORAS 2016

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - International Conference on Robotics, Automation and Sciences 2016

Y2 - 5 November 2016 through 6 November 2016

ER -