Adrian V. Dalca

research

∙ 05/04/2023

Neuralizer: General Neuroimage Analysis without Re-Training

Neuroimage processing tasks like segmentation, reconstruction, and regis...

0 Steffen Czolbe, et al. ∙

research

∙ 05/02/2023

Multi-Head Graph Convolutional Network for Structural Connectome Classification

We tackle classification based on brain connectivity derived from diffus...

0 Anees Kazi, et al. ∙

research

∙ 04/25/2023

Learning Task-Specific Strategies for Accelerated MRI

Compressed sensing magnetic resonance imaging (CS-MRI) seeks to recover ...

0 Zihui Wu, et al. ∙

research

∙ 04/19/2023

A robust and interpretable deep learning framework for multi-modal registration via keypoints

We present KeyMorph, a deep learning-based image registration framework ...

0 Alan Q. Wang, et al. ∙

research

∙ 04/12/2023

UniverSeg: Universal Medical Image Segmentation

While deep learning models have become the predominant method for medica...

0 Victor Ion Butoi, et al. ∙

research

∙ 03/02/2023

Joint cortical registration of geometry and function using semi-supervised learning

Brain surface-based image registration, an important component of brain ...

0 Jian Li, et al. ∙

research

∙ 01/26/2023

Anatomy-aware and acquisition-agnostic joint registration with SynthMorph

Affine image registration is a cornerstone of medical-image processing a...

0 Malte Hoffmann, et al. ∙

research

∙ 01/25/2023

Data Consistent Deep Rigid MRI Motion Correction

Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis...

0 Nalini M. Singh, et al. ∙

research

∙ 05/15/2022

SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration

In recent years, learning-based image registration methods have graduall...

0 Sean I. Young, et al. ∙

research

∙ 03/30/2022

Learning the Effect of Registration Hyperparameters with HyperMorph

We introduce HyperMorph, a framework that facilitates efficient hyperpar...

5 Andrew Hoopes, et al. ∙

research

∙ 03/18/2022

SynthStrip: Skull-Stripping for Any Brain Image

The removal of non-brain signal from magnetic resonance imaging (MRI) da...

0 Andrew Hoopes, et al. ∙

research

∙ 02/22/2022

Computing Multiple Image Reconstructions with a Single Hypernetwork

Deep learning based techniques achieve state-of-the-art results in a wid...

3 Alan Q. Wang, et al. ∙

research

∙ 02/07/2022

SUD: Supervision by Denoising for Medical Image Segmentation

Training a fully convolutional network for semantic segmentation typical...

5 Sean I. Young, et al. ∙

research

∙ 02/06/2022

Hyper-Convolutions via Implicit Kernels for Medical Imaging

The convolutional neural network (CNN) is one of the most commonly used ...

0 Tianyu Ma, et al. ∙

research

∙ 12/13/2021

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

Despite the superior performance of Deep Learning (DL) on numerous segme...

17 Sungmin Hong, et al. ∙

research

∙ 07/20/2021

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images

Image synthesis via Generative Adversarial Networks (GANs) of three-dime...

64 Sungmin Hong, et al. ∙

research

∙ 07/20/2021

SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution

Despite advances in data augmentation and transfer learning, convolution...

39 Benjamin Billot, et al. ∙

research

∙ 07/06/2021

Unsupervised learning of MRI tissue properties using MRI physics models

In neuroimaging, MRI tissue properties characterize underlying neurobiol...

14 Divya Varadarajan, et al. ∙

research

∙ 05/21/2021

Hyper-Convolution Networks for Biomedical Image Segmentation

The convolution operation is a central building block of neural network ...

0 Tianyu Ma, et al. ∙

research

∙ 05/13/2021

End-to-End Sequential Sampling and Reconstruction for MR Imaging

Accelerated MRI shortens acquisition time by subsampling in the measurem...

19 Tianwei Yin, et al. ∙

research

∙ 05/07/2021

Generative Adversarial Registration for Improved Conditional Deformable Templates

Deformable templates are essential to large-scale medical image registra...

5 Neel Dey, et al. ∙

research

∙ 03/04/2021

Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction

The impact of machine learning models on healthcare will depend on the d...

27 Aniruddh Raghu, et al. ∙

research

∙ 01/06/2021

Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks

Reconstructing under-sampled k-space measurements in Compressed Sensing ...

1 Alan Q. Wang, et al. ∙

research

∙ 01/04/2021

HyperMorph: Amortized Hyperparameter Learning for Image Registration

We present HyperMorph, a learning-based strategy for deformable image re...

13 Andrew Hoopes, et al. ∙

research

∙ 10/09/2020

Predictive Modeling of Anatomy with Genetic and Clinical Data

We present a semi-parametric generative model for predicting anatomy of ...

8 Adrian V. Dalca, et al. ∙

research

∙ 07/29/2020

Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data

Compressed Sensing MRI (CS-MRI) has shown promise in reconstructing unde...

16 Alan Q. Wang, et al. ∙

research

∙ 05/29/2020

Anatomical Predictions using Subject-Specific Medical Data

Changes over time in brain anatomy can provide important insight for tre...

9 Marianne Rakic, et al. ∙

research

∙ 04/29/2020

An Auto-Encoder Strategy for Adaptive Image Segmentation

Deep neural networks are powerful tools for biomedical image segmentatio...

8 Evan M. Yu, et al. ∙

research

∙ 04/21/2020

Learning Multi-Modal Image Registration without Real Data

We introduce a learning-based strategy for multi-modal registration of i...

7 Malte Hoffmann, et al. ∙

research

∙ 04/21/2020

Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

Partial voluming (PV) is arguably the last crucial unsolved problem in B...

5 Benjamin Billot, et al. ∙

research

∙ 03/23/2020

Learning a Probabilistic Strategy for Computational Imaging Sensor Selection

Optimized sensing is important for computational imaging in low-resource...

25 He Sun, et al. ∙

research

∙ 03/04/2020

A Learning Strategy for Contrast-agnostic MRI Segmentation

We present a deep learning strategy that enables, for the first time, co...

8 Benjamin Billot, et al. ∙

research

∙ 02/05/2020

ML4H Abstract Track 2019

A collection of the accepted abstracts for the Machine Learning for Heal...

0 Matthew B. A. McDermott, et al. ∙

research

∙ 01/04/2020

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

We introduce a new video synthesis task: synthesizing time lapse videos ...

16 Amy Zhao, et al. ∙

research

∙ 09/01/2019

Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions

We introduce visual deprojection: the task of recovering an image or vid...

3 Guha Balakrishnan, et al. ∙

research

∙ 08/13/2019

Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation

We tackle biomedical image segmentation in the scenario of only a few la...

7 Hyeon Woo Lee, et al. ∙

research

∙ 08/07/2019

Learning Conditional Deformable Templates with Convolutional Networks

We develop a learning framework for building deformable templates, which...

5 Adrian V. Dalca, et al. ∙

research

∙ 07/26/2019

Adaptive Compressed Sensing MRI with Unsupervised Learning

In compressed sensing MRI, k-space measurements are under-sampled to ach...

4 Cagla D. Bahadir, et al. ∙

research

∙ 07/01/2019

Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data

Registration is a core component of many imaging pipelines. In case of c...

0 Florian Dubost, et al. ∙

research

∙ 06/23/2019

Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

In classification applications, we often want probabilistic predictions ...

16 Adrian V. Dalca, et al. ∙

research

∙ 04/25/2019

Unsupervised deep learning for Bayesian brain MRI segmentation

Probabilistic atlas priors have been commonly used to derive adaptive an...

1 Adrian V. Dalca, et al. ∙

research

∙ 03/08/2019

Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Classical deformable registration techniques achieve impressive results ...

13 Adrian V. Dalca, et al. ∙

research

∙ 03/08/2019

Unsupervised Data Imputation via Variational Inference of Deep Subspaces

A wide range of systems exhibit high dimensional incomplete data. Accura...

11 Adrian V. Dalca, et al. ∙

research

∙ 03/07/2019

Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

We consider the problem of segmenting a biomedical image into anatomical...

3 Adrian V. Dalca, et al. ∙

research

∙ 02/25/2019

Data augmentation using learned transforms for one-shot medical image segmentation

Biomedical image segmentation is an important task in many medical appli...

33 Amy Zhao, et al. ∙

research

∙ 01/07/2019

Learning-based Optimization of the Under-sampling Pattern in MRI

Acquisition of Magnetic Resonance Imaging (MRI) scans can be accelerated...

1 Cagla Deniz Bahadir, et al. ∙

research

∙ 12/17/2018

Fast Learning-based Registration of Sparse Clinical Images

Deformable registration of clinical scans is a fundamental task for many...

1 Kathleen M. Lewis, et al. ∙

research

∙ 10/28/2018

Gaussian Process Prior Variational Autoencoders

Variational autoencoders (VAE) are a powerful and widely-used class of m...

1 Francesco Paolo Casale, et al. ∙

research

∙ 09/14/2018

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

We present VoxelMorph, a fast, unsupervised, learning-based algorithm fo...

1 Guha Balakrishnan, et al. ∙

research

∙ 09/11/2018

Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease

We propose a new iterative segmentation model which can be accurately le...

1 Danielle F. Pace, et al. ∙

Adrian V. Dalca

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