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Automated background segmentation for Rician noise estimation of noisy MR images

conference contribution
posted on 2023-05-23, 07:02 authored by Tran, VH, Jiang, D
The accurate estimation of Rician noise standard deviation is necessary for effective MR image denoising. In this short paper, we show that background segmentation is desirable for an accurate estimation of Rician noise parameter. Motivated by that observation an automated background segmentation algorithm is developed by combining morphological operations and active contour model in order to get more desired results. A test set MR images on 62 slices of human knee is used for illustration purpose. The proposed method is compared with some existing noise estimation methods and is shown to produce more accurate results.

History

Publication title

Proceedings of CIBEC2012

Editors

Ahmed Elbialy

Pagination

150-153

ISBN

978-1-4673-2800-5

Department/School

School of Engineering

Publisher

IEEE

Place of publication

Cairo, Egypt

Event title

The 6th Cairo International Conference on Biomedical Engineering

Event Venue

Cairo, Egypt

Date of Event (Start Date)

2012-12-20

Date of Event (End Date)

2012-12-22

Rights statement

Copyright 2012 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Diagnosis of human diseases and conditions

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