Nicha Dvornek, PhD
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About
Titles
Assistant Professor of Radiology and Biomedical Imaging
Appointments
Radiology & Biomedical Imaging
Assistant ProfessorPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Fellow
- Yale School of Medicine (2017)
- Postdoctoral Associate
- Yale School of Medicine (2015)
- PhD
- Yale University (2012)
- MPhil
- Yale University (2009)
- MS
- Yale University (2007)
- BS
- Johns Hopkins University (2006)
Research
Overview
Medical Subject Headings (MeSH)
Autistic Disorder; Biomedical Engineering; Brain; Image Processing, Computer-Assisted; Neural Networks, Computer
ORCID
0000-0002-1648-6055
Research at a Glance
Yale Co-Authors
Frequent collaborators of Nicha Dvornek's published research.
Publications Timeline
A big-picture view of Nicha Dvornek's research output by year.
Research Interests
Research topics Nicha Dvornek is interested in exploring.
James Duncan, PhD
Chi Liu, PhD
Lawrence Staib, PhD
Edward J Miller, MD, PhD
Albert Sinusas, MD
Ming-Kai Chen, MD, PhD
32Publications
1,010Citations
Brain
Image Processing, Computer-Assisted
Neural Networks, Computer
Publications
Featured Publications
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network
Guo X, Zhou B, Pigg D, Spottiswoode B, Casey ME, Liu C, Dvornek NC. Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. Medical Image Analysis 2022, 80: 102524. PMID: 35797734, PMCID: PMC10923189, DOI: 10.1016/j.media.2022.102524.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsConvolutional neural networkNeural networkConvolutional long short-term memory (ConvLSTM) layersDeep learning-based frameworkConvolutional long short-term memoryLong short-term memory layersDeep learning baselinesLong short-term memoryDynamic temporal featuresLearning-based frameworkDeep learning approachShort-term memory layersTracer distribution changeMotion estimation networkMotion prediction errorInference timeEstimation networkLearning baselinesNon-rigid registration methodLearning approachMotion correction methodMemory layerShort-term memoryTemporal featuresRegistration method
2024
TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchConceptsGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery diseaseChapter 13 Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI
Duncan J, Staib L, Dvornek N, Li X, Zhuang J, Wang J, Ventola P. Chapter 13 Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI. 2024, 357-393. DOI: 10.1016/b978-0-32-385124-4.00024-6.Peer-Reviewed Original ResearchConceptsLong short-term memoryGraph neural networksFunctional magnetic resonance imagingAutism spectrum disorderNeural ordinary differential equationsData-driven learning strategyDeep learning techniquesTask-based functional magnetic resonance imagingShort-term memoryNeural networkLearning techniquesImpaired social interactionTerm memoryBehavioral therapyRepetitive behaviorsSpectrum disorderDevelopmental disordersLearning strategiesSpatio-temporal characteristicsInherent dynamicsCharacterization of individualsModel of causalitySocial interactionNetworkPersonalized outcome predictions
2023
TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction
Guo X, Shi L, Chen X, Zhou B, Liu Q, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction. Lecture Notes In Computer Science 2023, 14288: 64-74. PMID: 38464964, PMCID: PMC10923183, DOI: 10.1007/978-3-031-44689-4_7.Peer-Reviewed Original ResearchCitationsLearning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation
Wang J, Dvornek N, Staib L, Duncan J. Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation. Lecture Notes In Computer Science 2023, 14312: 79-88. DOI: 10.1007/978-3-031-44858-4_8.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagesData augmentationClassification taskSpecific cognitive tasksMedical image analysisSynthetic data augmentationEffective data augmentationDownstream learning tasksCognitive tasksVariational autoencoder modelLearning taskTraining dataAutoencoder modelTemporal informationTraining datasetSequential informationSynthetic imagesTaskFMRI sequencesImage analysisMultiple perspectivesMagnetic resonance imagesImagesDifferent alternativesPersistent issueCopy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder
Dvornek N, Sullivan C, Duncan J, Gupta A. Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder. Lecture Notes In Computer Science 2023, 14312: 133-142. PMID: 38371906, PMCID: PMC10868600, DOI: 10.1007/978-3-031-44858-4_13.Peer-Reviewed Original ResearchMCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction
Guo X, Zhou B, Chen X, Chen M, Liu C, Dvornek N. MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction. IEEE Transactions On Medical Imaging 2023, 42: 3512-3523. PMID: 37368811, PMCID: PMC10751388, DOI: 10.1109/tmi.2023.3290003.Peer-Reviewed Original ResearchCitationsConceptsMotion estimation blockDeep learning benchmarksGood generalization capabilityMotion correctionMotion correction frameworkMotion prediction errorGeneralization capabilityNetwork performanceNeural networkMotion correction techniqueLearning benchmarksRegistration problemLoss functionEstimation blockLoss optimizationPenalty componentDynamic frameFitting errorSpatial alignmentParametric imagesSpatial misalignmentDynamic positron emission tomographySubject motionPrediction errorCorrection frameworkChapter 13 Deep learning with connectomes
Dvornek N, Li X. Chapter 13 Deep learning with connectomes. 2023, 289-308. DOI: 10.1016/b978-0-323-85280-7.00013-0.ChaptersCitationsConceptsDeep learning modelsLearning modelDeep learningClassic computer visionNeural network architectureImage analysis problemsMachine learning methodsNeural network modelComputer visionPotential future workNetwork architectureNonlinear neural network modelArt resultsPrediction taskLearning methodsNetwork modelAnalysis problemUseful representationConnectomePopular typeLearningFuture workData analysisArchitectureTask
2022
Inter-Pass Motion Correction for Whole-Body Dynamic PET and Parametric Imaging
Guo X, Wu J, Chen M, Liu Q, Onofrey J, Pucar D, Pang Y, Pigg D, Casey M, Dvornek N, Liu C. Inter-Pass Motion Correction for Whole-Body Dynamic PET and Parametric Imaging. IEEE Transactions On Radiation And Plasma Medical Sciences 2022, 7: 344-353. PMID: 37842204, PMCID: PMC10569406, DOI: 10.1109/trpms.2022.3227576.Peer-Reviewed Original ResearchCitationsConceptsMCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET
Guo X, Zhou B, Chen X, Liu C, Dvornek N. MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET. Lecture Notes In Computer Science 2022, 13434: 163-172. PMID: 38464686, PMCID: PMC10923180, DOI: 10.1007/978-3-031-16440-8_16.Peer-Reviewed Original ResearchCitationsConceptsConvolutional long short-term memory (ConvLSTM) layersLong short-term memory layersMotion estimation moduleShort-term memory layersDeep learning benchmarksEnhanced network performanceImage registration problemMotion correction frameworkMotion correctionU-NetNetwork performanceLearning benchmarksSimilarity measurementEstimation moduleRegistration problemGradient lossMemory layerLoss functionDynamic frameDynamic positron emission tomographyFitting errorSpatial alignmentSpatial misalignmentPatient motionModule
Clinical Trials
Current Trials
ACE Multisite Study of Adolescent & Adult Transitions
HIC ID2000024998RoleSub InvestigatorPrimary Completion Date04/30/2024Recruiting ParticipantsGenderBothAge12 years - 35 yearsCBT for Anxiety in Children With Autism
HIC ID1211011144RoleSub InvestigatorPrimary Completion Date06/30/2020Recruiting ParticipantsGenderBothAge8 years - 14 years
Academic Achievements and Community Involvement
honor Best Paper Award
International Award10th International Workshop on Machine Learning in Medical Imaging (MLMI 2019)Details10/13/2019Chinahonor Best Challenger Award
International AwardConnectomics in Neuroimaging - Transfer Learning ChallengeDetails10/13/2019Chinahonor James Hudson Brown – Alexander Brown Coxe Postdoctoral Fellowship
Yale School of Medicine AwardYale School of MedicineDetails07/01/2014United States
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The Anlyan Center
300 Cedar Street
New Haven, CT 06519