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07/21/2023
Generating Image-Specific Text Improves Fine-grained Image Classification
Recent vision-language models outperform vision-only models on many imag...
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07/13/2023
AnyStar: Domain randomized universal star-convex 3D instance segmentation
Star-convex shapes arise across bio-microscopy and radiology in the form...
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07/06/2023
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging
Most state-of-the-art techniques for medical image segmentation rely on ...
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05/04/2023
Neuralizer: General Neuroimage Analysis without Re-Training
Neuroimage processing tasks like segmentation, reconstruction, and regis...
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05/02/2023
Multi-Head Graph Convolutional Network for Structural Connectome Classification
We tackle classification based on brain connectivity derived from diffus...
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04/25/2023
Learning Task-Specific Strategies for Accelerated MRI
Compressed sensing magnetic resonance imaging (CS-MRI) seeks to recover ...
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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 ...
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04/12/2023
UniverSeg: Universal Medical Image Segmentation
While deep learning models have become the predominant method for medica...
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03/02/2023
Joint cortical registration of geometry and function using semi-supervised learning
Brain surface-based image registration, an important component of brain ...
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01/26/2023
Anatomy-aware and acquisition-agnostic joint registration with SynthMorph
Affine image registration is a cornerstone of medical-image processing a...
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01/25/2023
Data Consistent Deep Rigid MRI Motion Correction
Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis...
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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...
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03/30/2022
Learning the Effect of Registration Hyperparameters with HyperMorph
We introduce HyperMorph, a framework that facilitates efficient hyperpar...
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03/18/2022
SynthStrip: Skull-Stripping for Any Brain Image
The removal of non-brain signal from magnetic resonance imaging (MRI) da...
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02/22/2022
Computing Multiple Image Reconstructions with a Single Hypernetwork
Deep learning based techniques achieve state-of-the-art results in a wid...
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02/07/2022
SUD: Supervision by Denoising for Medical Image Segmentation
Training a fully convolutional network for semantic segmentation typical...
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02/06/2022
Hyper-Convolutions via Implicit Kernels for Medical Imaging
The convolutional neural network (CNN) is one of the most commonly used ...
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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...
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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...
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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...
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07/06/2021
Unsupervised learning of MRI tissue properties using MRI physics models
In neuroimaging, MRI tissue properties characterize underlying neurobiol...
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05/21/2021
Hyper-Convolution Networks for Biomedical Image Segmentation
The convolution operation is a central building block of neural network ...
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05/13/2021
End-to-End Sequential Sampling and Reconstruction for MR Imaging
Accelerated MRI shortens acquisition time by subsampling in the measurem...
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05/07/2021
Generative Adversarial Registration for Improved Conditional Deformable Templates
Deformable templates are essential to large-scale medical image registra...
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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...
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01/06/2021
Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks
Reconstructing under-sampled k-space measurements in Compressed Sensing ...
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01/04/2021
HyperMorph: Amortized Hyperparameter Learning for Image Registration
We present HyperMorph, a learning-based strategy for deformable image re...
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10/09/2020
Predictive Modeling of Anatomy with Genetic and Clinical Data
We present a semi-parametric generative model for predicting anatomy of ...
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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...
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05/29/2020
Anatomical Predictions using Subject-Specific Medical Data
Changes over time in brain anatomy can provide important insight for tre...
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04/29/2020
An Auto-Encoder Strategy for Adaptive Image Segmentation
Deep neural networks are powerful tools for biomedical image segmentatio...
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04/21/2020
Learning Multi-Modal Image Registration without Real Data
We introduce a learning-based strategy for multi-modal registration of i...
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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...
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03/23/2020
Learning a Probabilistic Strategy for Computational Imaging Sensor Selection
Optimized sensing is important for computational imaging in low-resource...
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03/04/2020
A Learning Strategy for Contrast-agnostic MRI Segmentation
We present a deep learning strategy that enables, for the first time, co...
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02/05/2020
ML4H Abstract Track 2019
A collection of the accepted abstracts for the Machine Learning for Heal...
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01/04/2020
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings
We introduce a new video synthesis task: synthesizing time lapse videos ...
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09/01/2019
Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions
We introduce visual deprojection: the task of recovering an image or vid...
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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...
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08/07/2019
Learning Conditional Deformable Templates with Convolutional Networks
We develop a learning framework for building deformable templates, which...
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07/26/2019
Adaptive Compressed Sensing MRI with Unsupervised Learning
In compressed sensing MRI, k-space measurements are under-sampled to ach...
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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...
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06/23/2019
Confidence Calibration for Convolutional Neural Networks Using Structured Dropout
In classification applications, we often want probabilistic predictions ...
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04/25/2019
Unsupervised deep learning for Bayesian brain MRI segmentation
Probabilistic atlas priors have been commonly used to derive adaptive an...
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03/08/2019
Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces
Classical deformable registration techniques achieve impressive results ...
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03/08/2019
Unsupervised Data Imputation via Variational Inference of Deep Subspaces
A wide range of systems exhibit high dimensional incomplete data. Accura...
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03/07/2019
Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation
We consider the problem of segmenting a biomedical image into anatomical...
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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...
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01/07/2019
Learning-based Optimization of the Under-sampling Pattern in MRI
Acquisition of Magnetic Resonance Imaging (MRI) scans can be accelerated...
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12/17/2018