Adrian V. Dalca

Orcid: 0000-0002-8422-0136

Affiliations:
  • Harvard Medical School, USA


According to our database1, Adrian V. Dalca authored at least 110 papers between 2008 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Boosting Skull-Stripping Performance for Pediatric Brain Images.
CoRR, 2024

Tyche: Stochastic In-Context Learning for Medical Image Segmentation.
CoRR, 2024

AnyStar: Domain randomized universal star-convex 3D instance segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
A robust and interpretable deep learning framework for multi-modal registration via keypoints.
Medical Image Anal., December, 2023

Hyper-convolutions via implicit kernels for medical image analysis.
Medical Image Anal., May, 2023

SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining.
Medical Image Anal., May, 2023

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023

ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Medical Image.
CoRR, 2023

JOSA: Joint surface-based registration and atlas construction of brain geometry and function.
CoRR, 2023

Generating Image-Specific Text Improves Fine-grained Image Classification.
CoRR, 2023

Learning Task-Specific Strategies for Accelerated MRI.
CoRR, 2023

Non-Proportional Parametrizations for Stable Hypernetwork Learning.
CoRR, 2023

Amortized Learning of Dynamic Feature Scaling for Image Segmentation.
CoRR, 2023

Anatomy-aware and acquisition-agnostic joint registration with SynthMorph.
CoRR, 2023

Scale-Space Hypernetworks for Efficient Biomedical Image Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Anatomy-specific acquisition-agnostic affine registration learned from fictitious images.
Proceedings of the Medical Imaging 2023: Image Processing, 2023

Data Consistent Deep Rigid MRI Motion Correction.
Proceedings of the Medical Imaging with Deep Learning, 2023

Joint cortical registration of geometry and function using semi-supervised learning.
Proceedings of the Medical Imaging with Deep Learning, 2023

AngioMoCo: Learning-Based Motion Correction in Cerebral Digital Subtraction Angiography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Multi-head Graph Convolutional Network for Structural Connectome Classification.
Proceedings of the Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology, 2023

UniverSeg: Universal Medical Image Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neuralizer: General Neuroimage Analysis without Re-Training.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
SynthMorph: Learning Contrast-Invariant Registration Without Acquired Images.
IEEE Trans. Medical Imaging, 2022

How Machine Learning is Powering Neuroimaging to Improve Brain Health.
Neuroinformatics, 2022

SynthStrip: skull-stripping for any brain image.
NeuroImage, 2022

Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease.
Medical Image Anal., 2022

Learning the Effect of Registration Hyperparameters with HyperMorph.
CoRR, 2022

Computing Multiple Image Reconstructions with a Single Hypernetwork.
CoRR, 2022

SUD: Supervision by Denoising for Medical Image Segmentation.
CoRR, 2022

Hyper-Convolutions via Implicit Kernels for Medical Imaging.
CoRR, 2022

SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration.
Proceedings of the Biomedical Image Registration - 10th International Workshop, 2022

Hyper-Convolution Networks for Biomedical Image Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

KeyMorph: Robust Multi-modal Affine Registration via Unsupervised Keypoint Detection.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

TopoFit: Rapid Reconstruction of Topologically-Correct Cortical Surfaces.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021
Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer - ASEG and SAMSEG.
NeuroImage, 2021

Mapping the subcortical connectivity of the human default mode network.
NeuroImage, 2021

A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images.
NeuroImage, 2021

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels.
CoRR, 2021

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.
CoRR, 2021

SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution.
CoRR, 2021

Unsupervised learning of MRI tissue properties using MRI physics models.
CoRR, 2021

End-to-End Sequential Sampling and Reconstruction for MR Imaging.
CoRR, 2021

Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks.
CoRR, 2021

End-to-End Sequential Sampling and Reconstruction for MRI.
Proceedings of the Machine Learning for Health, 2021

HyperRecon: Regularization-Agnostic CS-MRI Reconstruction with Hypernetworks.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images.
Proceedings of the Deep Generative Models, and Data Augmentation, Labelling, and Imperfections, 2021

Learning Mri Contrast-Agnostic Registration.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Joint Segmentation Of Multiple Sclerosis Lesions And Brain Anatomy In MRI Scans Of Any Contrast And Resolution With CNNs.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

HyperMorph: Amortized Hyperparameter Learning for Image Registration.
Proceedings of the Information Processing in Medical Imaging, 2021

Generative Adversarial Registration for Improved Conditional Deformable Templates.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Learning to predict with supporting evidence: applications to clinical risk prediction.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020
Deep-Learning-Based Optimization of the Under-Sampling Pattern in MRI.
IEEE Trans. Computational Imaging, 2020

Cortical surface registration using unsupervised learning.
NeuroImage, 2020

Automated segmentation of the hypothalamus and associated subunits in brain MRI.
NeuroImage, 2020

Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation.
Medical Image Anal., 2020

Joint Frequency- and Image-Space Learning for Fourier Imaging.
CoRR, 2020

Anatomical Predictions using Subject-Specific Medical Data.
CoRR, 2020

Learning Multi-Modal Image Registration without Real Data.
CoRR, 2020

Cortical surface registration using unsupervised learning.
CoRR, 2020

ML4H Abstract Track 2019.
CoRR, 2020

An Auto-Encoder Strategy for Adaptive Image Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

A Learning Strategy for Contrast-agnostic MRI Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Learning Conditional Deformable Shape Templates for Brain Anatomy.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

Neural Network-Based Reconstruction in Compressed Sensing MRI Without Fully-Sampled Training Data.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2020

3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Unbiased Atlas Construction for Neonatal Cortical Surfaces via Unsupervised Learning.
Proceedings of the Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis, 2020

Partial Volume Segmentation of Brain MRI Scans of Any Resolution and Contrast.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Learning a Probabilistic Strategy for Computational Imaging Sensor Selection.
Proceedings of the 2020 IEEE International Conference on Computational Photography, 2020

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Fast learning-based registration of sparse 3D clinical images.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

2019
Medical Image Imputation From Image Collections.
IEEE Trans. Medical Imaging, 2019

VoxelMorph: A Learning Framework for Deformable Medical Image Registration.
IEEE Trans. Medical Imaging, 2019

Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces.
Medical Image Anal., 2019

Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation.
CoRR, 2019

Adaptive Compressed Sensing MRI with Unsupervised Learning.
CoRR, 2019

Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data.
CoRR, 2019

Confidence Calibration for Convolutional Neural Networks Using Structured Dropout.
CoRR, 2019

Unsupervised Data Imputation via Variational Inference of Deep Subspaces.
CoRR, 2019

Data augmentation using learned transforms for one-shot medical image segmentation.
CoRR, 2019

Learning Conditional Deformable Templates with Convolutional Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?
Proceedings of the Machine Learning for Health Workshop, 2019

Unsupervised Deep Learning for Bayesian Brain MRI Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Learning-Based Optimization of the Under-Sampling Pattern in MRI.
Proceedings of the Information Processing in Medical Imaging, 2019

Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Reconstructing Video of Time-Varying Sources From Radio Interferometric Measurements.
IEEE Trans. Computational Imaging, 2018

Fast Learning-based Registration of Sparse Clinical Images.
CoRR, 2018

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.
CoRR, 2018

Gaussian Process Prior Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

An Unsupervised Learning Model for Deformable Medical Image Registration.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Synthesizing Images of Humans in Unseen Poses.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Reconstructing Video from Interferometric Measurements of Time-Varying Sources.
CoRR, 2017

Frequency Diffeomorphisms for Efficient Image Registration.
Proceedings of the Information Processing in Medical Imaging, 2017

Population Based Image Imputation.
Proceedings of the Information Processing in Medical Imaging, 2017

2016
Genetic, clinical and population priors for brain images.
PhD thesis, 2016

Patch-Based Discrete Registration of Clinical Brain Images.
Proceedings of the Patch-Based Techniques in Medical Imaging, 2016

2015
Interactive Whole-Heart Segmentation in Congenital Heart Disease.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Predictive Modeling of Anatomy with Genetic and Clinical Data.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

2014
Segmentation of Cerebrovascular Pathologies in Stroke Patients with Spatial and Shape Priors.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013
Quantification and Analysis of Large Multimodal Clinical Image Studies: Application to Stroke.
Proceedings of the Multimodal Brain Image Analysis - Third International Workshop, 2013

Joint Modeling of Imaging and Genetics.
Proceedings of the Information Processing in Medical Imaging, 2013

2011
Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

2010
VARiD: A variation detection framework for color-space and letter-space platforms.
Bioinform., 2010

Genome variation discovery with high-throughput sequencing data.
Briefings Bioinform., 2010

2009
SHRiMP: Accurate Mapping of Short Color-space Reads.
PLoS Comput. Biol., 2009

2008
FRESCO: Flexible Alignment with Rectangle Scoring Schemes.
Proceedings of the Biocomputing 2008, 2008


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