2024
Cross noise level PET denoising with continuous adversarial domain generalization
Liu X, Eslahi S, Marin T, Tiss A, Chemli Y, Huang Y, Johnson K, Fakhri G, Ouyang J. Cross noise level PET denoising with continuous adversarial domain generalization. Physics In Medicine And Biology 2024, 69: 085001. PMID: 38484401, PMCID: PMC11195012, DOI: 10.1088/1361-6560/ad341a.Peer-Reviewed Original ResearchDomain generalization techniqueDomain generalizationDenoising performanceSuperior denoising performanceLatent feature representationGeneral techniqueDistribution shiftsAdversarial trainingDenoised imageFeature representationDomain labelsDistribution divergenceNoise levelDeep learningImage spaceDenoisingPerformance degradationCore ideaNoise realizationsCD methodNoiseImage volumesPerformanceImagesPSNR
2019
Bulk motion detection and correction using list-mode data for cardiac PET imaging
Sun T, Petibon Y, Han P, Ma C, Kim S, Alpert N, Fakhri G, Ouyang J. Bulk motion detection and correction using list-mode data for cardiac PET imaging. Proceedings Of SPIE--the International Society For Optical Engineering 2019, 11072: 110722f-110722f-5. DOI: 10.1117/12.2534701.Peer-Reviewed Original ResearchList-mode dataCardiac PET imagingPET list-mode dataMotion-corrected imagesLines of responsePET imaging applicationsCardiac PETImage qualityBulk motionCardiac PET studiesMotion correctionPET imagingBrain PETMotion estimationData-driven approachMotion detectionImaging applicationsImage spaceMoving frameStatic reference frameMotion transformationCorrectionCenter positionMotionReference frame
2018
End-to-End Lung Nodule Detection in Computed Tomography
Wu D, Kim K, Dong B, Fakhri G, Li Q. End-to-End Lung Nodule Detection in Computed Tomography. Lecture Notes In Computer Science 2018, 11046: 37-45. DOI: 10.1007/978-3-030-00919-9_5.Peer-Reviewed Original ResearchDeep reconstruction networkLung nodule detectionReconstruction networkEnd-to-end detectorMedical imagesLung Image Database Consortium image collectionNodule detectionEfficient network trainingReconstructed imagesConvolutional neural networkEnd-to-endSuperior detection performanceRaw dataComputer visionCAD systemCNN detectorNetwork trainingImage collectionNeural networkDetection performanceImage spaceDetection taskDetection systemModern medical imagingFanbeam projections
2015
PET Point Spread Function Modeling and Image Deblurring Using a PET/MRI Joint Entropy Prior
Dutta J, Fakhri G, Zhu X, Li Q. PET Point Spread Function Modeling and Image Deblurring Using a PET/MRI Joint Entropy Prior. 2015, 1423-1426. DOI: 10.1109/isbi.2015.7164143.Peer-Reviewed Original ResearchJoint entropyDe-blurring techniqueImage deblurringBrain WebQuantitative accuracy of PETImage spaceEfficient frameworkDeconvolution problemDeblurringCost functionPoint spread function modelPenalty functionHuman datasetsSpatial resolution capabilitiesPET scannerAmplifier noisePET imagingImagesConsistent with MRIQuantitative accuracyPartial volume effectsPhantomDatasetEntropyFunction model