2017
Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study
Cappabianco F, Lellis L, Miranda P, Ide J, Mujica-Parodi L. Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study. Lecture Notes In Computer Science 2017, 10125: 459-466. DOI: 10.1007/978-3-319-52277-7_56.Peer-Reviewed Original ResearchEdge detection methodImage processing applicationsAutomatic edge detection methodDetection methodAccuracy of stateComputer visionNon-uniform intensityEdge detectionProcessing applicationsFundamental operationIntensity inhomogeneityHigh accuracyNumber of worksUltra-high field magnetic resonance imagingAccuracyGradient maximaCannyCase studyInhomogeneity correctionVisionRobustSmall numberBrain edgesMethodEdge
2016
High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction
Lam F, Ma C, Clifford B, Johnson C, Liang Z. High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction. Magnetic Resonance In Medicine 2016, 76: spcone-spcone. DOI: 10.1002/mrm.26460.Peer-Reviewed Original ResearchImage reconstructionSubspace structureSpectroscopic imaging sequenceSubspace modelImage sequencesEdge-preserving regularizationReconstruction methodThrough-plane resolutionData acquisitionImage reconstruction methodIn-planeIn vivo brain experimentsEncoding schemeField inhomogeneity correctionIn-plane resolutionTwo-dimensional (2DImaging frameworkInhomogeneity correctionData setsSubspaceHybrid data setsSpectroscopic imagingSpatial resolutionBrain experimentsImages
2015
High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction
Lam F, Ma C, Clifford B, Johnson C, Liang Z. High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction. Magnetic Resonance In Medicine 2015, 76: 1059-1070. PMID: 26509928, PMCID: PMC4848237, DOI: 10.1002/mrm.26019.Peer-Reviewed Original ResearchConceptsSubspace structureSpectroscopic imaging sequenceImage reconstructionSubspace modelImage sequencesImage reconstruction purposesEdge-preserving regularizationData acquisitionReconstruction methodThrough-plane resolutionImage reconstruction methodIn-planeIn vivo brain experimentsEncoding schemeField inhomogeneity correctionIn-plane resolutionTwo-dimensional (2DImaging frameworkInhomogeneity correctionData setsSubspaceHigh-resolutionHybrid data setsSpatial resolutionBrain experimentsImproved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and <inline-formula><tex-math notation="LaTeX">$B_0$</tex-math></inline-formula> Field Inhomogeneity
Liu Y, Ma C, Clifford B, Lam F, Johnson C, Liang Z. Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and$B_0$ Peer-Reviewed Original ResearchConceptsLow-rank filterSignal-to-noise ratioConstrained Cramer-RaoDenoising MRSI dataFiltering methodLow-rank modelCramer-RaoDenoising performanceRank minimizationHigh-resolution magnetic resonance spectroscopic imagingBoundary constraintsIn vivo MRSI dataData corruptionLow-rankMRSI dataFilterNoiseUpper boundB0 field inhomogeneityField inhomogeneity correctionDenoisingField inhomogeneityInhomogeneity correctionMethodMagnetic resonance spectroscopic imaging
2005
TU‐FF‐A2‐03: Effects of CT Calibration On Tissue Inhomogeneity Correction in Radiotherapy
Song H, Chen Z, Ahmad M, Deng J, Fan Y, Nath R. TU‐FF‐A2‐03: Effects of CT Calibration On Tissue Inhomogeneity Correction in Radiotherapy. Medical Physics 2005, 32: 2115-2115. DOI: 10.1118/1.1998474.Peer-Reviewed Original ResearchTissue inhomogeneity correctionsCT calibration curveInhomogeneity correctionCT calibrationDose calculationElectron density relative to waterDetermination of electron densityCT number errorDose calculation errorsGE Light SpeedMV beamRadiation beamLight speedField sizeElectron densityLow-kVNumber errorHigh-kVPhysical thicknessBeamCortical boneCalculationsKVCorrectionDensity of water
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