Nicha Dvornek, PhD
Assistant Professor of Radiology and Biomedical ImagingDownloadHi-Res Photo
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About
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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
Publications Timeline
A big-picture view of Nicha Dvornek's research output by year.
Yale Co-Authors
Frequent collaborators of Nicha Dvornek's published research.
Research Interests
Research topics Nicha Dvornek is interested in exploring.
39Publications
1,138Citations
James Duncan, PhD
Chi Liu, PhD
Lawrence Staib, PhD
Edward J Miller, MD, PhD
Albert Sinusas, MD
Denis Sukhodolsky, PhD
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
Deep Learning-based Dynamic PET Intra-frame Motion Correction and Integration with Inter-frame Motion Estimation
Guo X, Tsai Y, Liu Q, Guo L, Valadez G, Dvornek N, Liu C. Deep Learning-based Dynamic PET Intra-frame Motion Correction and Integration with Inter-frame Motion Estimation. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657268.Peer-Reviewed Original ResearchConceptsIntra-frame motionMotion correctionGated imagesLearning-based registration approachesDeep learning-based worksInter-frame motion estimationConventional image registrationLearning-based worksImage registrationMotion estimation processMotion estimation frameworkInter-frame registrationRespiratory gatingImprove image sharpnessInter-frameInference timeMotion estimationReconstructed framesDynamic PET datasetsGeneralization abilityPET imagingConventional registrationDynamic PET imagesImprove image qualityComputational inefficiencyCLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-Tuning
Du Y, Chang B, Dvornek N. CLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-Tuning. Lecture Notes In Computer Science 2024, 15012: 465-475. DOI: 10.1007/978-3-031-72390-2_44.Peer-Reviewed Original ResearchConceptsContrastive Language-Image Pre-trainingLanguage modelState-of-the-art performanceSelf-supervised representation learningContrastive learning methodFine-tuningProlonged training timeBERT encoderContrastive learningRepresentation learningClass labelsGPU resourcesTraining samplesTraining timeMammography datasetModel sizePre-trainingLearning methodsEfficient frameworkVisual modelRichness of informationDatasetClinical diagnostic dataLearningMedical applicationsPrior knowledge-guided vision-transformer-based unsupervised domain adaptation for intubation prediction in lung disease at one week
Yang J, Henao J, Dvornek N, He J, Bower D, Depotter A, Bajercius H, de Mortanges A, You C, Gange C, Ledda R, Silva M, Dela Cruz C, Hautz W, Bonel H, Reyes M, Staib L, Poellinger A, Duncan J. Prior knowledge-guided vision-transformer-based unsupervised domain adaptation for intubation prediction in lung disease at one week. Computerized Medical Imaging And Graphics 2024, 102442. DOI: 10.1016/j.compmedimag.2024.102442.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationSpatial prior informationDomain adaptationLabeled dataData-driven approachUnsupervised domain adaptation modelMedical image analysis tasksImage analysis tasksTransformer-based modelsMedical image analysisPrior informationOutcome prediction tasksAdversarial trainingDistribution alignmentDomain shiftAttention headsClass tokenPoor generalizationAnalysis tasksTarget domainPrediction taskData distributionKnowledge-guidedLocal weightsMedical imagesMine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels
You C, Dai W, Liu F, Min Y, Dvornek N, Li X, Clifton D, Staib L, Duncan J. Mine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Transactions On Pattern Analysis And Machine Intelligence 2024, PP: 1-16. PMID: 39269798, DOI: 10.1109/tpami.2024.3461321.Peer-Reviewed Original ResearchCitationsConceptsMedical image segmentationImage segmentationMedical image segmentation frameworkContext of medical image segmentationLong-tailed class distributionStrong data augmentationsIntra-class variationsSemi-supervised settingData imbalance issueImage segmentation frameworkMedical image analysisMedical image dataSupervision signalsContrastive learningBenchmark datasetsUnsupervised mannerLabel setsData augmentationSegmentation frameworkDomain expertisePseudo-codeImbalance issueModel trainingMedical imagesSegmentation modelCascaded multi-path shortcut diffusion model for medical image translation
Zhou Y, Chen T, Hou J, Xie H, Dvornek N, Zhou S, Wilson D, Duncan J, Liu C, Zhou B. Cascaded multi-path shortcut diffusion model for medical image translation. Medical Image Analysis 2024, 98: 103300. PMID: 39226710, DOI: 10.1016/j.media.2024.103300.Peer-Reviewed Original ResearchConceptsGenerative adversarial networkMedical image translationImage translationState-of-the-art methodsImage-to-image translationMedical image datasetsImage translation tasksImage-to-imageState-of-the-artMedical image processingHigh-quality translationsUncertainty estimationCascaded pipelineAdversarial networkImage datasetsSub-tasksTranslation qualityTranslation performanceTranslation tasksImage processingTranslation resultsDM methodPrior imageRobust performanceExperimental resultsSpectral Brain Graph Neural Network for Prediction of Anxiety in Children with Autism Spectrum Disorder
Duan P, Dvornek N, Wang J, Eilbott J, Du Y, Sukhodolsky D, Duncan J. Spectral Brain Graph Neural Network for Prediction of Anxiety in Children with Autism Spectrum Disorder. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635753.Peer-Reviewed Original ResearchConceptsGraph neural networksFunctional magnetic resonance imagingAutism spectrum disorderNeural networkCurrent graph neural networksSpectrum disorderMASC-2Spectral analysis algorithmAnalysis algorithmGraph-based networkMultidimensional Anxiety ScaleFast Fourier transformPredictive of anxietyDaily anxiety levelsExtract hidden informationBrain functional networksPower spectrum densityNode featuresNetwork performanceComorbid anxietyBrain mechanismsHidden informationCorrelated featuresAnxiety ScaleTotal scoreTAI-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 diseaseSIFT-DBT: Self-Supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification
Du Y, Hooley R, Lewin J, Dvornek N. SIFT-DBT: Self-Supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2024, 00: 1-5. PMID: 39263046, PMCID: PMC11386909, DOI: 10.1109/isbi56570.2024.10635723.Peer-Reviewed Original ResearchChapter 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 ResearchCitationsConceptsLong 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
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 & 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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