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Nicha Dvornek, PhD

Assistant Professor

Contact Information

Nicha Dvornek, PhD

Office Location

Research Summary

My research is on the development and application of machine learning algorithms for medical image analysis and processing. My current work focuses on deep learning methods for learning from functional magnetic resonance imaging data with application to autism spectrum disorders. I am driven by the ultimate goal of better understanding neurological disorders and diseases to achieve more personalized medicine.

Coauthors

Research Interests

Autistic Disorder; Biomedical Engineering; Brain; Image Processing, Computer-Assisted; Neural Networks, Computer

Selected Publications

  • Inter-pass motion correction for whole-body dynamic PET and parametric imagingGuo 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, PP: 1-1. DOI: 10.1109/trpms.2022.3227576.
  • MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PETGuo X, Zhou B, Chen X, Liu C, Dvornek N. MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET 2022, 13434: 163-172. DOI: 10.1007/978-3-031-16440-8_16.
  • Characterization of Early Stage Parkinson's Disease From Resting-State fMRI Data Using a Long Short-Term Memory NetworkGuo X, Tinaz S, Dvornek N. Characterization of Early Stage Parkinson's Disease From Resting-State fMRI Data Using a Long Short-Term Memory Network Frontiers In Neuroimaging 2022, 1: 952084. DOI: 10.3389/fnimg.2022.952084.
  • Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal ModelingZhuang J, Dvornek N, Tatikonda S, Papademetris X, Ventola P, Duncan J. Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling 2021, 12729: 58-70. DOI: 10.1007/978-3-030-78191-0_5.
  • A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder SeverityWang S, Dvornek N. A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder Severity 2021, 00: 1338-1341. DOI: 10.1109/isbi48211.2021.9434009.
  • Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content SpaceYang J, Li X, Pak D, Dvornek N, Chapiro J, Lin M, Duncan J. Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space 2020, 12444: 52-61. DOI: 10.1007/978-3-030-60548-3_6.
  • Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion CorrectionGuo Y, Dvornek N, Lu Y, Tsai Y, Hamill J, Casey M, Liu C. Deep Learning based Respiratory Pattern Classification and Applications in PET/CT Motion Correction 2019, 00: 1-5. DOI: 10.1109/nss/mic42101.2019.9059783.
  • ShelfNet for Fast Semantic SegmentationZhuang J, Yang J, Gu L, Dvornek N. ShelfNet for Fast Semantic Segmentation 2019, 00: 847-856. DOI: 10.1109/iccvw.2019.00113.
  • Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree BaggingDvornek, N.C., Yang, D., Venkataraman, A., Ventola, P., Staib, L.H., Pelphrey, K.A., Duncan, J.S., “Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging,” In: Sixth International Workshop on Multimodal Learning for Clinical Decision Support, 2016.

Clinical Trials

ConditionsStudy Title
Children's Health; Men's Health; Mental Health & Behavioral Research; Women's HealthACE Multisite Study of Adolescent & Adult Transitions
Child Development & Autism; Children's Health; Mental Health & Behavioral ResearchCBT for Anxiety in Children With Autism