2025
Increasing angular sampling for dedicated cardiac SPECT scanner: Implementation with Deep Learning and Validation with human data
Xie H, Alashi A, Thorn S, Chen X, Zhou B, Sinusas A, Liu C. Increasing angular sampling for dedicated cardiac SPECT scanner: Implementation with Deep Learning and Validation with human data. Journal Of Nuclear Cardiology 2025, 102168. PMID: 39986346, DOI: 10.1016/j.nuclcard.2025.102168.Peer-Reviewed Original Research
2024
Deep Learning and visual search: Using raw eye movement data, convolutional neural networks generate target-location predictions in line with experimental manipulations
Crotty N, Massa N, Grubb M. Deep Learning and visual search: Using raw eye movement data, convolutional neural networks generate target-location predictions in line with experimental manipulations. Journal Of Vision 2024, 24: 951. DOI: 10.1167/jov.24.10.951.Peer-Reviewed Original ResearchEvaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data*
Ellis C, Miller R, Calhoun V. Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data*. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-5. PMID: 40039441, DOI: 10.1109/embc53108.2024.10782103.Peer-Reviewed Original ResearchConceptsAugmented training setData augmentationTraining setDA methodsDeep learning methodsDA approachNeuropsychiatric disorder diagnosisModel performanceTraining dataDeep learningEEG datasetDataset sizeLearning methodsAugmentation approachImprove model performanceDepressive disorder diagnosisDA efficacyDatasetDisorder diagnosisCompare performanceMajor depressive disorder diagnosisPerformanceBaseline setDeepChannelCalibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
You C, Min Y, Dai W, Sekhon J, Staib L, Duncan J. Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2024, 00: 26140-26150. PMID: 39640960, PMCID: PMC11620289, DOI: 10.1109/cvpr52733.2024.02470.Peer-Reviewed Original ResearchDiverse downstream tasksVision-language modelsPre-trained modelsRepresentation of samplesContrastive learningDownstream tasksFeature reweightingTraining dataFeature patternsModel generalizationGroup annotationsPain pointsGroup labelsAnnotationRobustnessClassifierClipsFeaturesDeepDeploymentBenchmarksTime-intensiveCodeTaskLearningMonte-Carlo Frequency Dropout for Predictive Uncertainty Estimation in Deep Learning
Zeevi T, Venkataraman R, Staib L, Onofrey J. Monte-Carlo Frequency Dropout for Predictive Uncertainty Estimation in Deep Learning. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635511.Peer-Reviewed Original ResearchArtificial neural networkState-of-the-artMedical image dataPredictive uncertainty estimationBiomedical image dataImage dataOptimal artificial neural networkMC dropoutDropout approachSource-codeDrop-connectDeep learningNeural networkSignal spaceMonte-CarloPrediction uncertaintyUncertainty estimationDiverse setComprehensive comparisonPrediction scenariosDeepPosterior predictive distributionRepositoryDecision-makingNetworkHigh‐resolution extracellular pH imaging of liver cancer with multiparametric MR using Deep Image Prior
Dong S, Shewarega A, Chapiro J, Cai Z, Hyder F, Coman D, Duncan J. High‐resolution extracellular pH imaging of liver cancer with multiparametric MR using Deep Image Prior. NMR In Biomedicine 2024, 37: e5145. PMID: 38488205, DOI: 10.1002/nbm.5145.Peer-Reviewed Original ResearchDeep Image PriorU-NetUnsupervised deep learning techniquesU-Net parametersDeep learning techniquesHigh-resolution ground truthU-Net architectureSuper-resolution imagingImage priorsSuper-resolutionGround truthMean absolute errorDeepSpatial resolutionPostprocessing methodDeep imagingAbsolute errorImagesAnatomical MR imagesMR spectroscopic imagingAnatomical informationSpectroscopic imagingInformationAcquisition timeError
2022
A Social Robot for Anxiety Reduction via Deep Breathing
Matheus K, Vázquez M, Scassellati B. A Social Robot for Anxiety Reduction via Deep Breathing. 2022, 00: 89-94. DOI: 10.1109/ro-man53752.2022.9900638.Peer-Reviewed Original Research
2018
Super-Resolution PET Using A Very Deep Convolutional Neural Network
Song T, Chowdhury S, Kim K, Gong K, Fakhri G, Li Q, Dutta J. Super-Resolution PET Using A Very Deep Convolutional Neural Network. 2018, 00: 1-2. DOI: 10.1109/nssmic.2018.8824683.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkSuper-resolution convolutional neural networkDeep convolutional neural networkImage deblurring approachesInput image patchesBlur kernelResolution recovery techniquesSpatial location informationDeblurring approachDeblurring processImage patchesQuantitative accuracy of PETLocation informationSpatially-varying natureSuperior performanceNetworkRecovery techniquesDigital phantomDeblurringBrainWebInformationPartial volume effectsDeepBlurPenalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting
Kim K, Wu D, Gong K, Dutta J, Kim J, Son Y, Kim H, Fakhri G, Li Q. Penalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting. IEEE Transactions On Medical Imaging 2018, 37: 1478-1487. PMID: 29870375, PMCID: PMC6375088, DOI: 10.1109/tmi.2018.2832613.Peer-Reviewed Original ResearchConceptsDeep learningDenoising convolutional neural networkConvolutional neural networkDeep learning-basedPerformance of iterative reconstructionPotential of deep learningDeep networksNoise levelLearning-basedReconstruction frameworkDegradation of performanceNeural networkDnCNNMedical imagesDownsampled dataFitness functionPoisson thinningFull-dose imagesLow dose imagesNoise conditionsNetworkImage qualityPET reconstructionDose imagesDeep
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