2024
Monte-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-makingNetwork
2023
Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fontaine K, Fang X, Revilla E, Lu Y, Onofrey J. Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38111738, PMCID: PMC10725741, DOI: 10.1109/isbi53787.2023.10230791.Peer-Reviewed Original ResearchMulti-task deep learningMulti-task architectureMonte Carlo dropoutTesting subjectsDeep learningMotion tracking deviceSupervised learningMotion correction methodNetwork predictionHead motion correctionAppearance predictionReconstructed imagesPrediction performanceImage acquisitionImage qualityTracking deviceMotion correctionLearning processUncertainty estimationTomography image acquisitionHead motionPrediction uncertaintyLearningQualitative resultsArchitecture