2023
Successive Subspace Learning for Cardiac Disease Classification with Two-Phase Deformation Fields from Cine MRI
Liu X, Xing F, Gaggin H, Kuo C, El Fakhri G, Woo J. Successive Subspace Learning for Cardiac Disease Classification with Two-Phase Deformation Fields from Cine MRI. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38031559, PMCID: PMC10686280, DOI: 10.1109/isbi53787.2023.10230746.Peer-Reviewed Original ResearchTraining samplesCardiovascular disease classificationCNN-based approachDeep learning modelsCardiac disease classificationSubspace learningSSL modelClassification performanceDeep learningCardiac cine magnetic resonance imagingSubspace approximationSupervised regressionLearning modelsAccurate characterization resultsDisease classificationClassificationCardiac atlasLearningDeformation fieldEnd-systolic phaseFrameworkFeedforward designPerformanceTrainingSSLSynthesizing audio from tongue motion during speech using tagged MRI via transformer
Liu X, Xing F, Prince J, Stone M, Fakhri G, Woo J. Synthesizing audio from tongue motion during speech using tagged MRI via transformer. Proceedings Of SPIE--the International Society For Optical Engineering 2023, 12464: 1246410-1246410-5. PMID: 38009135, PMCID: PMC10669779, DOI: 10.1117/12.2653345.Peer-Reviewed Original ResearchMotion fieldAudio waveformAdversarial training approachImprove synthesis qualityConvolutional decoderAudio dataSynthesis qualityTranslation networkData structureSpeech waveformTemporal modelTagged MRITongue motionTraining approachSpectrogramMuscle deformationSource of informationSpeechIntelligible speechFrameworkDecodingInformationPredictive informationEncodingNetwork
2022
Cmri2spec: Cine MRI Sequence to Spectrogram Synthesis via A Pairwise Heterogeneous Translator
Liu X, Xing F, Stone M, Prince J, Kim J, El Fakhri G, Woo J. Cmri2spec: Cine MRI Sequence to Spectrogram Synthesis via A Pairwise Heterogeneous Translator. 2013 IEEE International Conference On Acoustics, Speech And Signal Processing 2022, 00: 1481-1485. PMID: 36212702, PMCID: PMC9544268, DOI: 10.1109/icassp43922.2022.9746381.Peer-Reviewed Original ResearchMultimodal representation learningAdversarial training approachCine MRI sequencesCNN encoderRepresentation learningConvolutional decoderAdversarial networkDataset sizeSequence encodingEnhance realismHeterogeneous translationSpeech wordsSynthesis frameworkTraining approachExperimental resultsEncodingSynthesis accuracySpectrogramFrameworkDecodingAdversarial Non-local Multi-modality MRI Aggregation for Directional DWI Synthesis
Liu X, Xing F, Wedeen V, Fakhri G, Woo J. Adversarial Non-local Multi-modality MRI Aggregation for Directional DWI Synthesis. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2022 DOI: 10.58530/2022/3449.Peer-Reviewed Original ResearchTagged-MRI to audio synthesis with a pairwise heterogeneous deep translator
Liu X, Xing F, Stone M, Prince J, Kim J, Fakhri G, Woo J. Tagged-MRI to audio synthesis with a pairwise heterogeneous deep translator. The Journal Of The Acoustical Society Of America 2022, 151: a133-a133. DOI: 10.1121/10.0010891.Peer-Reviewed Original ResearchLatent space featuresEncoder-decoder structureCNN-based encoderSpace featuresDeep learning frameworkTagged MRI sequencesKullback-Leibler divergenceMel-spectrogramSpeech-related disordersLearning frameworkAudio synthesisAudio waveformSpeech productionKullback-LeiblerHeterogeneous representationsEvaluation strategiesIntelligible speechFrameworkTagged-MRISpeechDecodingAudioVisual movementEncodingUtterancesSelf-Semantic Contour Adaptation for Cross Modality Brain Tumor Segmentation
Liu X, Xing F, Fakhri G, Woo J. Self-Semantic Contour Adaptation for Cross Modality Brain Tumor Segmentation. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2022, 00: 1-5. PMID: 35990931, PMCID: PMC9387767, DOI: 10.1109/isbi52829.2022.9761629.Peer-Reviewed Original ResearchUnsupervised domain adaptationAdaptive networkLow-level edge informationCross-domain alignmentEnhance segmentation performanceMulti-task frameworkCross-modality segmentationSegmentation of brain tumorsAdversarial learningDomain adaptationSemantic segmentationEdge informationSemantic alignmentPrecursor taskSegmentation performanceSpatial informationNetworkSemantic adaptationMagnetic resonance imagingTaskContour adaptationBraTS2018InformationFrameworkAdaptation
2021
Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
Liu X, Xing F, Yang C, El Fakhri G, Woo J. Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation. Lecture Notes In Computer Science 2021, 12902: 549-559. PMID: 34734216, PMCID: PMC8562716, DOI: 10.1007/978-3-030-87196-3_51.Peer-Reviewed Original ResearchUnsupervised domain adaptationSegmentation taskSource domainTarget domainUnsupervised domain adaptation methodsLabeled source domainSource domain dataUnsupervised learning methodDomain adaptationUDA methodsPrivacy issuesLearning methodsAdaptation frameworkDomain dataData storageTransfer knowledgeBatch statisticsSource dataOptimization objectivesAdaptation stageTaskFrameworkPrivacyDomainBraTSDomain Generalization under Conditional and Label Shifts via Variational Bayesian Inference
Liu X, Hu B, Jin L, Han X, Xing F, Ouyang J, Lu J, El Fakhri G, Woo J. Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference. 2021, 881-887. DOI: 10.24963/ijcai.2021/122.Peer-Reviewed Original ResearchDomain generalizationDomain-invariant feature learningVariational Bayesian inference frameworkLabel shiftCross-domain accuracyLabeled source domainVariational Bayesian inferenceFeature learningBayesian inference frameworkLatent spaceSource domainTarget domainDistribution matchingTransfer knowledgeInference frameworkSuperior performanceP(x|yBayesian inferenceLabelingDomainFrameworkGeneralizationBenchmarksPosterior alignmentLearningA Unified Conditional Disentanglement Framework For Multimodal Brain Mr Image Translation
Liu X, Xing F, Fakhri G, Woo J. A Unified Conditional Disentanglement Framework For Multimodal Brain Mr Image Translation. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2021, 00: 10-14. PMID: 34567419, PMCID: PMC8460116, DOI: 10.1109/isbi48211.2021.9433897.Peer-Reviewed Original Research
2019
Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning
Gong K, Han P, Fakhri G, Ma C, Li Q. Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning. NMR In Biomedicine 2019, 35: e4224. PMID: 31865615, PMCID: PMC7306418, DOI: 10.1002/nbm.4224.Peer-Reviewed Original ResearchConceptsSignal-to-noise ratioImage denoisingReconstruction frameworkDeep learning-based image denoisingDeep learning-based denoisersMR image denoisingLearning-based denoisingLow signal-to-noise ratioK-space dataNoisy imagesTraining labelsTraining pairsNetwork inputNeural networkDenoisingIn vivo experiment dataSuperior performanceImaging speedReconstruction processImage qualityLong imaging timesNetworkFrameworkImagesSpatial resolutionMAPEM-Net: an unrolled neural network for Fully 3D PET image reconstruction
Gong K, Wu D, Kim K, Yang J, Sun T, Fakhri G, Seo Y, Li Q. MAPEM-Net: an unrolled neural network for Fully 3D PET image reconstruction. Proceedings Of SPIE--the International Society For Optical Engineering 2019, 11072: 110720o-110720o-5. DOI: 10.1117/12.2534904.Peer-Reviewed Original ResearchPET image reconstructionNeural networkImage reconstructionImage denoising applicationDeep neural networksNeural network frameworkConvolutional neural networkDenoising applicationsDenoising methodNetwork frameworkUpdate stepData consistencyIll-posedNetworkClinical datasetsInverse problemMAPEMFrameworkAlgorithmDatasetDetected photonsReconstructionMethodSimulationEMnet: an unrolled deep neural network for PET image reconstruction
Gong K, Wu D, Kim K, Yang J, Fakhri G, Seo Y, Li Q. EMnet: an unrolled deep neural network for PET image reconstruction. Progress In Biomedical Optics And Imaging 2019, 10948: 1094853-1094853-6. DOI: 10.1117/12.2513096.Peer-Reviewed Original ResearchDeep neural networksPET image reconstructionNeural networkExpectation maximizationImage reconstructionImage denoising applicationNeural network frameworkNeural network denoisersDenoising applicationsDenoising methodNetwork denoisingNetwork trainingNetwork frameworkWhole graphUpdate stepData consistencyIll-posedNetworkInverse problemEMNETDenoisingSimulated dataFrameworkAlgorithmGraph