Cardiac MRI steam images denoising using bayes classifier

A. G. Motaal; M. A. Al-Attar; N. F. Osman; A. S. Fahmy

doi:10.1109/CIBEC.2008.4786056

Cardiac MRI steam images denoising using bayes classifier

A. G. Motaal, M. A. Al-Attar, N. F. Osman, A. S. Fahmy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Imaging of the heart anatomy and function using magnetic resonance imaging (MRI) is an important diagnosis tool for heart diseases. Several techniques have been developed to increase the contrast-to-noise ratio (CNR) between myocardium and background. Recently, a technique that acquires cine cardiac images with black-blood contrast has been proposed. Although the technique produces cine sequence of high contrast, it suffers from elevated noise which limits the CNR. In this paper, we study the performance and efficiency of applying a Bayes classifier to remove background noise. Real MRI data is used to test and validate the proposed method; In addition, a quantitative comparison is done between the proposed method and other thresholding-based classifications techniques.

Original language	English (US)
Title of host publication	2008 Cairo International Biomedical Engineering Conference, CIBEC 2008
DOIs	https://doi.org/10.1109/CIBEC.2008.4786056
State	Published - 2008
Externally published	Yes
Event	2008 Cairo International Biomedical Engineering Conference, CIBEC 2008 - Cairo, Egypt Duration: Dec 18 2008 → Dec 20 2008

Publication series

Name	2008 Cairo International Biomedical Engineering Conference, CIBEC 2008

Other

Other	2008 Cairo International Biomedical Engineering Conference, CIBEC 2008
Country/Territory	Egypt
City	Cairo
Period	12/18/08 → 12/20/08

ASJC Scopus subject areas

Biomedical Engineering

Access to Document

10.1109/CIBEC.2008.4786056

Cite this

Motaal, AG, Al-Attar, MA, Osman, NF & Fahmy, AS 2008, Cardiac MRI steam images denoising using bayes classifier. in 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008., 4786056, 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008, 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008, Cairo, Egypt, 12/18/08. https://doi.org/10.1109/CIBEC.2008.4786056

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title = "Cardiac MRI steam images denoising using bayes classifier",

abstract = "Imaging of the heart anatomy and function using magnetic resonance imaging (MRI) is an important diagnosis tool for heart diseases. Several techniques have been developed to increase the contrast-to-noise ratio (CNR) between myocardium and background. Recently, a technique that acquires cine cardiac images with black-blood contrast has been proposed. Although the technique produces cine sequence of high contrast, it suffers from elevated noise which limits the CNR. In this paper, we study the performance and efficiency of applying a Bayes classifier to remove background noise. Real MRI data is used to test and validate the proposed method; In addition, a quantitative comparison is done between the proposed method and other thresholding-based classifications techniques.",

author = "Motaal, {A. G.} and Al-Attar, {M. A.} and Osman, {N. F.} and Fahmy, {A. S.}",

year = "2008",

doi = "10.1109/CIBEC.2008.4786056",

language = "English (US)",

isbn = "9781424426959",

series = "2008 Cairo International Biomedical Engineering Conference, CIBEC 2008",

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T1 - Cardiac MRI steam images denoising using bayes classifier

AU - Motaal, A. G.

AU - Al-Attar, M. A.

AU - Osman, N. F.

AU - Fahmy, A. S.

PY - 2008

Y1 - 2008

N2 - Imaging of the heart anatomy and function using magnetic resonance imaging (MRI) is an important diagnosis tool for heart diseases. Several techniques have been developed to increase the contrast-to-noise ratio (CNR) between myocardium and background. Recently, a technique that acquires cine cardiac images with black-blood contrast has been proposed. Although the technique produces cine sequence of high contrast, it suffers from elevated noise which limits the CNR. In this paper, we study the performance and efficiency of applying a Bayes classifier to remove background noise. Real MRI data is used to test and validate the proposed method; In addition, a quantitative comparison is done between the proposed method and other thresholding-based classifications techniques.

AB - Imaging of the heart anatomy and function using magnetic resonance imaging (MRI) is an important diagnosis tool for heart diseases. Several techniques have been developed to increase the contrast-to-noise ratio (CNR) between myocardium and background. Recently, a technique that acquires cine cardiac images with black-blood contrast has been proposed. Although the technique produces cine sequence of high contrast, it suffers from elevated noise which limits the CNR. In this paper, we study the performance and efficiency of applying a Bayes classifier to remove background noise. Real MRI data is used to test and validate the proposed method; In addition, a quantitative comparison is done between the proposed method and other thresholding-based classifications techniques.

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U2 - 10.1109/CIBEC.2008.4786056

DO - 10.1109/CIBEC.2008.4786056

M3 - Conference contribution

AN - SCOPUS:63649094265

SN - 9781424426959

T3 - 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008

BT - 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008

T2 - 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008

Y2 - 18 December 2008 through 20 December 2008

ER -

Cardiac MRI steam images denoising using bayes classifier

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