Nicha C. Dvornek

Orcid: 0000-0002-1648-6055

Affiliations:
  • Yale University, New Haven, CT, USA


According to our database1, Nicha C. Dvornek authored at least 52 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

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.
CoRR, 2024

2023
MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction.
IEEE Trans. Medical Imaging, December, 2023

FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction.
IEEE Trans. Medical Imaging, 2023

Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation.
Proceedings of the Machine Learning in Clinical Neuroimaging - 6th International Workshop, 2023

TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2023

Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder.
Proceedings of the Machine Learning in Clinical Neuroimaging - 6th International Workshop, 2023

2022
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network.
Medical Image Anal., 2022

Early Disease Stage Characterization in Parkinson's Disease from Resting-state fMRI Data Using a Long Short-term Memory Network.
CoRR, 2022

MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Surrogate Gap Minimization Improves Sharpness-Aware Training.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning.
IEEE Trans. Medical Imaging, 2021

Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge.
Medical Image Anal., 2021

BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis.
Medical Image Anal., 2021

Momentum Centering and Asynchronous Update for Adaptive Gradient Methods.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder Severity.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling.
Proceedings of the Information Processing in Medical Imaging, 2021

MALI: A memory efficient and reverse accurate integrator for Neural ODEs.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification.
IEEE Trans. Medical Imaging, 2020

Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results.
Medical Image Anal., 2020

Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge.
CoRR, 2020

AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space.
Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020

Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

Graph embedding using Infomax for ASD classification and brain functional difference detection.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Estimating Reproducible Functional Networks Associated with Task Dynamics Using Unsupervised LSTMS.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making.
CoRR, 2019

Invertible Network for Classification and Biomarker Selection for ASD.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Graph Neural Network for Interpreting Task-fMRI Biomarkers.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Prediction of Treatment Outcome for Autism from Structure of the Brain Based On Sure Independence Screening.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery.
Proceedings of the Information Processing in Medical Imaging, 2019

ShelfNet for Fast Semantic Segmentation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Decision explanation and feature importance for invertible networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Domain-Agnostic Learning With Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging.
CoRR, 2018

Prediction of Severity and Treatment Outcome for ASD from fMRI.
Proceedings of the PRedictive Intelligence in MEdicine - First International Workshop, 2018

Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2-Channel convolutional 3D deep neural network (2CC3D) for fMRI analysis: ASD classification and feature learning.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Combining phenotypic and resting-state fMRI data for autism classification with recurrent neural networks.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks.
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

2012
Tracking Metastatic Brain Tumors in Longitudinal Scans via Joint Image Registration and Labeling.
Proceedings of the Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data, 2012

2011
Registration of brain resection MRI with intensity and location priors.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Non-rigid registration of longitudinal brain tumor treatment MRI.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

2010
Non-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

Pairwise registration of images with missing correspondences due to resection.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

2007
C-arm calibration: is it really necessary?
Proceedings of the Medical Imaging 2007: Visualization and Image-Guided Procedures, 2007


  Loading...