Search results for " rf-inhomogeneity"

showing 3 items of 3 documents

Volumetric Bias Correction

2007

This paper presents a method to suppress the bias artifact, also known as RF-inhomogeneity, in Magnetic Resonance Imaging (MRI). This artifact produces illumination variations due to magnetic field fluctuations of the device. In the latest years many works have been devoted to face this problem. In this work we present the 3D version of a new approach to bias correction, which is called Exponential Entropy Driven Homomorphic Unsharp Masking (E2D-HUM). This technique has been already presented by some of the authors for the 2D case only. The description of the whole method is detailed, and some experimental results are reported.

Artifact (error)business.industryComputer scienceEntropy drivenHomomorphic encryptionBias artifact Rf-inhomogeneity MRIExponential functionMagnetic fieldFace (geometry)Bias correctionComputer visionArtificial intelligencebusinessUnsharp masking
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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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Exponential Entropy Driven HUM on Knee MR Images

2007

A very important artifact corrupting Magnetic Resonance Images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present a measure based on information theory with a large experimental setup aimed to demonstrate the validity of our approach.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryEntropy Knee Magnetic resonance rf-inhomogeneityImage segmentationInformation theoryExponential functionHomomorphic filteringHumEntropy (information theory)SegmentationComputer visionArtificial intelligenceMr imagesbusinessMathematics2005 IEEE Engineering in Medicine and Biology 27th Annual Conference
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