Adrian V. Dalca

verfied profile

MIT and HMS. Machine Learning for Health and computer vision.

http://adalca.mit.edu

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

Biomedical image segmentation is an important task in many medical appli...
02/25/2019 ∙ by Amy Zhao, et al. ∙ 33 ∙ share

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Learning a Probabilistic Strategy for Computational Imaging Sensor Selection

Optimized sensing is important for computational imaging in low-resource...
03/23/2020 ∙ by He Sun, et al. ∙ 25 ∙ share

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Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

In classification applications, we often want probabilistic predictions ...
06/23/2019 ∙ by Zhilu Zhang, et al. ∙ 16 ∙ share

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Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

We introduce a new video synthesis task: synthesizing time lapse videos ...
01/04/2020 ∙ by Amy Zhao, et al. ∙ 16 ∙ share

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Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Classical deformable registration techniques achieve impressive results ...
03/08/2019 ∙ by Adrian V. Dalca, et al. ∙ 13 ∙ share

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Unsupervised Data Imputation via Variational Inference of Deep Subspaces

A wide range of systems exhibit high dimensional incomplete data. Accura...
03/08/2019 ∙ by Adrian V. Dalca, et al. ∙ 11 ∙ share

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

We tackle biomedical image segmentation in the scenario of only a few la...
08/13/2019 ∙ by Hyeon Woo Lee, et al. ∙ 7 ∙ share

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A Learning Strategy for Contrast-agnostic MRI Segmentation

We present a deep learning strategy that enables, for the first time, co...
03/04/2020 ∙ by Benjamin Billot, et al. ∙ 7 ∙ share

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Learning Conditional Deformable Templates with Convolutional Networks

We develop a learning framework for building deformable templates, which...
08/07/2019 ∙ by Adrian V. Dalca, et al. ∙ 5 ∙ share

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Adaptive Compressed Sensing MRI with Unsupervised Learning

In compressed sensing MRI, k-space measurements are under-sampled to ach...
07/26/2019 ∙ by Cagla D. Bahadir, et al. ∙ 4 ∙ share

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Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

We consider the problem of segmenting a biomedical image into anatomical...
03/07/2019 ∙ by Adrian V. Dalca, et al. ∙ 3 ∙ share

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Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions

We introduce visual deprojection: the task of recovering an image or vid...
09/01/2019 ∙ by Guha Balakrishnan, et al. ∙ 3 ∙ share

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Reconstructing Video from Interferometric Measurements of Time-Varying Sources

Very long baseline interferometry (VLBI) makes it possible to recover im...
11/03/2017 ∙ by Katherine L. Bouman, et al. ∙ 1 ∙ share

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An Unsupervised Learning Model for Deformable Medical Image Registration

We present an efficient learning-based algorithm for deformable, pairwis...
02/07/2018 ∙ by Guha Balakrishnan, et al. ∙ 1 ∙ share

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Synthesizing Images of Humans in Unseen Poses

We address the computational problem of novel human pose synthesis. Give...
04/20/2018 ∙ by Guha Balakrishnan, et al. ∙ 1 ∙ share

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Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

Traditional deformable registration techniques achieve impressive result...
05/11/2018 ∙ by Adrian V. Dalca, et al. ∙ 1 ∙ share

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Medical Image Imputation from Image Collections

We present an algorithm for creating high resolution anatomically plausi...
08/17/2018 ∙ by Adrian V. Dalca, et al. ∙ 1 ∙ share

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

We propose a new iterative segmentation model which can be accurately le...
09/11/2018 ∙ by Danielle F. Pace, et al. ∙ 1 ∙ share

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VoxelMorph: A Learning Framework for Deformable Medical Image Registration

We present VoxelMorph, a fast, unsupervised, learning-based algorithm fo...
09/14/2018 ∙ by Guha Balakrishnan, et al. ∙ 1 ∙ share

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Gaussian Process Prior Variational Autoencoders

Variational autoencoders (VAE) are a powerful and widely-used class of m...
10/28/2018 ∙ by Francesco Paolo Casale, et al. ∙ 1 ∙ share

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Fast Learning-based Registration of Sparse Clinical Images

Deformable registration of clinical scans is a fundamental task for many...
12/17/2018 ∙ by Kathleen M. Lewis, et al. ∙ 1 ∙ share

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

Acquisition of Magnetic Resonance Imaging (MRI) scans can be accelerated...
01/07/2019 ∙ by Cagla Deniz Bahadir, et al. ∙ 1 ∙ share

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Unsupervised deep learning for Bayesian brain MRI segmentation

Probabilistic atlas priors have been commonly used to derive adaptive an...
04/25/2019 ∙ by Adrian V. Dalca, et al. ∙ 1 ∙ share

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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...
07/01/2019 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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ML4H Abstract Track 2019

A collection of the accepted abstracts for the Machine Learning for Heal...
02/05/2020 ∙ by Matthew B. A. McDermott, et al. ∙ 0 ∙ share

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Adrian V. Dalca

Featured Co-authors

William T. Freeman

Marleen de Bruijne

Mert R. Sabuncu

Polina Golland

Fredo Durand

John Guttag

Florian Dubost

Tristan Naumann

Koen Van Leemput

Wiro Niessen

Guha Balakrishnan

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

Learning a Probabilistic Strategy for Computational Imaging Sensor Selection

Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Unsupervised Data Imputation via Variational Inference of Deep Subspaces

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

A Learning Strategy for Contrast-agnostic MRI Segmentation

Learning Conditional Deformable Templates with Convolutional Networks

Adaptive Compressed Sensing MRI with Unsupervised Learning

Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions

Reconstructing Video from Interferometric Measurements of Time-Varying Sources

An Unsupervised Learning Model for Deformable Medical Image Registration

Synthesizing Images of Humans in Unseen Poses

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

Medical Image Imputation from Image Collections

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

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

Gaussian Process Prior Variational Autoencoders

Fast Learning-based Registration of Sparse Clinical Images

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

Unsupervised deep learning for Bayesian brain MRI segmentation

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

ML4H Abstract Track 2019