2022
Supervised Deep Learning for Head Motion Correction in PET
Zeng T, Zhang J, Revilla E, Lieffrig E, Fang X, Lu Y, Onofrey J. Supervised Deep Learning for Head Motion Correction in PET. Lecture Notes In Computer Science 2022, 13434: 194-203. PMID: 38107622, PMCID: PMC10725740, DOI: 10.1007/978-3-031-16440-8_19.Peer-Reviewed Original ResearchDeep learning-based algorithmMotion tracking informationHead motion correctionNovel deep learningLearning-based algorithmMotion correctionDeep learningRegression layerEncoder layersTracking hardwareNetwork performanceSupervised mannerTracking informationAblation studiesRegistration approachCloud representationBrain positron emission tomography (PET) imagingTransformation layerDesign choicesReconstructed imagesPrediction performanceExternal devicesImage analysisTransformation parametersHead motion
2011
Direct 3D PET Image Reconstruction into MR Image Space
Gravel P, Verhaeghe J, Reader A. Direct 3D PET Image Reconstruction into MR Image Space. 2011, 3955-3962. DOI: 10.1109/nssmic.2011.6153752.Peer-Reviewed Original ResearchImage spaceTransformation parametersPET image reconstructionRigid body transformation parametersDifferent image spacesImage resolution degradationMotion correctionQuality of reconstructionRegistration transformation parametersReconstruction frameworkAbsolute error analysisImage registrationMean absolute errorInterpolation effectRegistration methodImage reconstructionImage resolutionFinal imageMLEM algorithmScanner geometrySimilarity criteriaAbsolute errorSpatial atlasDirect reconstructionImages
2008
Calculation of the confidence intervals for transformation parameters in the registration of medical images
Bansal R, Staib LH, Laine AF, Xu D, Liu J, Posecion LF, Peterson BS. Calculation of the confidence intervals for transformation parameters in the registration of medical images. Medical Image Analysis 2008, 13: 215-233. PMID: 19138877, PMCID: PMC2891652, DOI: 10.1016/j.media.2008.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceConfidence IntervalsCorpus CallosumData Interpretation, StatisticalHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSimilarity transformationMultivariate GaussianLeast squares estimationTransformation parametersMathematical frameworkRandom variablesPresence of noiseCovariance matrixLandmark pointsQuantifying errorsSimilarity parameterAmount of misregistrationInherent technological limitationsAmount of noiseGaussianCoordinatesInevitable errorsReal-world datasetsFunctional relationAmount of blurErrorParametersWorld datasetsNoiseConfidence intervals
2003
Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation
Bansal R, Staib LH, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan JS. Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation. IEEE Transactions On Medical Imaging 2003, 22: 29. PMID: 12703758, DOI: 10.1109/tmi.2002.806430.Peer-Reviewed Original ResearchConceptsRegistration frameworkImage dataMutual information-based registration algorithmRegistration parametersPortal imagesUltrasound image dataReal patient dataTomography image dataImage pixelsPixel correlationRegistration algorithmPatient setup verificationSegmentationPixel intensityMarkov random processInitial versionTransformation parametersAppropriate entropyImagesAlgorithmPatient dataFrameworkCT imagesLine processSetup verification
1999
Entropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation
Bansal R, Staib L, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan J. Entropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation. Lecture Notes In Computer Science 1999, 1679: 567-578. DOI: 10.1007/10704282_61.Peer-Reviewed Original ResearchPatient setup verificationPortal imagesReal patient dataSingle portal imagePose parametersCT data setsRegistration frameworkRegistration parametersSetup verificationDifferent initializationsAlgorithmMultiple portalsIterative fashionData setsTransformation parametersAppropriate entropyImagesCT dataPatient dataVerificationNoise conditionsFrameworkSegmentationAccurate estimationInitialization
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply