Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator
Liu X, Xing F, Prince J, Zhuo J, Stone M, El Fakhri G, Woo J. Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator. Lecture Notes In Computer Science 2022, 13436: 376-386. PMID: 36820764, PMCID: PMC9942274, DOI: 10.1007/978-3-031-16446-0_36.Peer-Reviewed Original ResearchAudio waveformEnd-to-end deep learning frameworkAdversarial training approachDeep learning frameworkEnd-to-endTwo-dimensional spectrogramAdversarial networkIntermediate representationLearning frameworkResidual attentionDisentanglement strategyAudio synthesisDataset sizeImprove realismHeterogeneous representationsHeterogeneous translationAttentional strategiesTraining approachExperimental resultsMuscle deformationIntelligible speechMotor control theoriesTagged-MRIRelated-disordersSpeech acousticsCmri2spec: 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 accuracySpectrogramFrameworkDecodingVoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI
Liu X, Xing F, Yang C, Kuo C, Babu S, Fakhri G, Jenkins T, Woo J. VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI. IEEE Journal Of Biomedical And Health Informatics 2022, 26: 1128-1139. PMID: 34339378, PMCID: PMC8807766, DOI: 10.1109/jbhi.2021.3097735.Peer-Reviewed Original ResearchConceptsConvolutional neural networkLearning modelsDimension reductionSubspace learning modelConcatenation of featuresState-of-the-artUnsupervised dimension reductionDeep learning modelsMedical image dataSupervised dimension reductionImage dataClassification of amyotrophic lateral sclerosisSubspace learningClassification taskDeep learningDataset sizeNeural networkSubspace approximationMemory requirementsTraining datasetClassification approachAUC scoreAccurate classificationDatasetExperimental results