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Fetal magnetic resonance image denoising based on homogeneity testing and Non Local Means

Haris, K. LU ; Kantasis, G. ; Maglaveras, N. and Aletras, A. H. LU orcid (2016) 42nd Computing in Cardiology Conference, 2015 42. p.341-344
Abstract

A novel edge-preserving denoising method for MR images is proposed. Local statistical homogeneity testing is combined with the well-known for structure preserving properties, Non Local Means (NLM) denoising method. The detection of homogeneity reduces remarkably the computational effort required by NLM which is applied only to information-rich image areas. Preliminary qualitative results on fetal and cardiac MR images are shown. These initial results are positive proving the effective noise reduction with less computational load.

Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Computing in Cardiology
volume
42
article number
7408656
pages
4 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
42nd Computing in Cardiology Conference, 2015
conference location
Nice, France
conference dates
2015-09-06 - 2015-09-09
external identifiers
  • scopus:84964077792
ISBN
9781509006854
DOI
10.1109/CIC.2015.7408656
language
English
LU publication?
no
id
a6430c87-cca7-4cb6-9848-faa4a814606e
date added to LUP
2016-06-28 14:41:48
date last changed
2022-01-30 04:47:57
@inproceedings{a6430c87-cca7-4cb6-9848-faa4a814606e,
  abstract     = {{<p>A novel edge-preserving denoising method for MR images is proposed. Local statistical homogeneity testing is combined with the well-known for structure preserving properties, Non Local Means (NLM) denoising method. The detection of homogeneity reduces remarkably the computational effort required by NLM which is applied only to information-rich image areas. Preliminary qualitative results on fetal and cardiac MR images are shown. These initial results are positive proving the effective noise reduction with less computational load.</p>}},
  author       = {{Haris, K. and Kantasis, G. and Maglaveras, N. and Aletras, A. H.}},
  booktitle    = {{Computing in Cardiology}},
  isbn         = {{9781509006854}},
  language     = {{eng}},
  month        = {{02}},
  pages        = {{341--344}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Fetal magnetic resonance image denoising based on homogeneity testing and Non Local Means}},
  url          = {{http://dx.doi.org/10.1109/CIC.2015.7408656}},
  doi          = {{10.1109/CIC.2015.7408656}},
  volume       = {{42}},
  year         = {{2016}},
}