Adaptive method for MRI enhancement using squared eigenfunctions of the Schrödinger operator

Abderrazak Chahid, Hacene Serrai, Eric Achten, Taous-Meriem Laleg-Kirati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Recently, a Magnetic Resonance image denoising method, based on squared eigenfunctions of the Schrödinger operator, has been presented. However, its performance depends on the choice of a filtering parameter called h. We propose an adaptive selection of the filtering parameter by a grid segmentation of the noisy input image. The latter will follow an appropriate distribution along the different sub-images allowing the adaptation of its value to the spatial variation of noise and responded efficiently to the denoising objectives. Numerical tests using a synthetic dataset from BrainWeb and real MR images show the effectiveness of the proposed approach compared to the standard case with one fixed parameter.
Original languageEnglish (US)
Title of host publication2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Print)9781509058037
DOIs
StatePublished - Apr 11 2018

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