Search results for " homomorphic unsharp masking"

showing 2 items of 2 documents

Illumination correction on biomedical images

2014

RF-Inhomogeneity Correction (aka bias) artifact is an important re- search field in Magnetic Resonance Imaging (MRI). Bias corrupts MR images alter- ing their illumination even though they are acquired with the most recent scanners. Homomorphic Unsharp Masking (HUM) is a filtering technique aimed at correcting illumination inhomogeneity, but it produces a halo around the edges as a side effect. In this paper a novel correction scheme based on HUM is proposed to correct the artifact mentioned above without introducing the halo. A wide experimentation has been performed on MR images. The method has been tuned and evaluated using the simulated Brainweb image database. In this framework, the ap…

RF-inhomogeneity MRI magnetic resonance homomorphic unsharp masking bias artifactSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
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Morphological exponential entropy driven-HUM.

2006

This paper presents an improvement to the Ex- ponential Entropy Driven - Homomorphic Unsharp Masking (E 2 D − HUM ) algorithm devoted to illumination artifact sup- pression on Magnetic Resonance Images. E 2 D−HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E 2 D − HUM without a segmentation phase, whose parameters should be chosen in relation to the image. I. INTRODUCTION Most of the studies on illumination correction found in literature are oriented to brain (18) magnetic resonance images (…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPolynomialArtifact (error)Brain MappingMRI rf-inhomogeneity homomorphic unsharp masking bias artifactbusiness.industryEntropyModels NeurologicalStreakBrainImage segmentationInformation theoryExpectation–maximization algorithmImage Processing Computer-AssistedHumansComputer visionSegmentationArtificial intelligencebusinessArtifactsAlgorithmAlgorithmsUnsharp maskingMathematics
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