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Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation
Class imbalance poses a challenge for developing unbiased, accurate pred...
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Atlas-ISTN: Joint Segmentation, Registration and Atlas Construction with Image-and-Spatial Transformer Networks
Deep learning models for semantic segmentation are able to learn powerfu...
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Hierarchical Gaussian Processes with Wasserstein-2 Kernels
We investigate the usefulness of Wasserstein-2 kernels in the context of...
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Cranial Implant Design via Virtual Craniectomy with Shape Priors
Cranial implant design is a challenging task, whose accuracy is crucial ...
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Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
Decompressive craniectomy (DC) is a common surgical procedure consisting...
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Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
We introduce Post-DAE, a post-processing method based on denoising autoe...
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Deep Structural Causal Models for Tractable Counterfactual Inference
We formulate a general framework for building structural causal models (...
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Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
In image segmentation, there is often more than one plausible solution f...
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Unpaired Multi-modal Segmentation via Knowledge Distillation
Multi-modal learning is typically performed with network architectures c...
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Causality matters in medical imaging
This article discusses how the language of causality can shed new light ...
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Universal Adversarial Perturbations to Understand Robustness of Texture vs. Shape-biased Training
Convolutional Neural Networks (CNNs) used on image classification tasks ...
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Domain Generalization via Model-Agnostic Learning of Semantic Features
Generalization capability to unseen domains is crucial for machine learn...
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Vertebrae Detection and Localization in CT with Two-Stage CNNs and Dense Annotations
We propose a new, two-stage approach to the vertebrae centroid detection...
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Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects
This is an empirical study to investigate the impact of scanner effects ...
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Needles in Haystacks: On Classifying Tiny Objects in Large Images
In some computer vision domains, such as medical or hyperspectral imagin...
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Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
Overfitting in deep learning has been the focus of a number of recent wo...
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Is Texture Predictive for Age and Sex in Brain MRI?
Deep learning builds the foundation for many medical image analysis task...
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Image-and-Spatial Transformer Networks for Structure-Guided Image Registration
Image registration with deep neural networks has become an active field ...
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Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels
Accurate, automated lesion detection in Computed Tomography (CT) is an i...
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Quantitative Error Prediction of Medical Image Registration using Regression Forests
Predicting registration error can be useful for evaluation of registrati...
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Graph Convolutional Gaussian Processes
We propose a novel Bayesian nonparametric method to learn translation-in...
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Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing
We investigate discrete spin transformations, a geometric framework to m...
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FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
We present a new approach to diffeomorphic non-rigid registration of med...
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Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
Background: The trend towards large-scale studies including population i...
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PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation
Deep convolutional networks have demonstrated the state-of-the-art perfo...
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Towards continual learning in medical imaging
This work investigates continual learning of two segmentation tasks in b...
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Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning
Revealing latent structure in data is an active field of research, havin...
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Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images
We propose a novel attention gate (AG) model for medical image analysis ...
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Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes
Accurate and robust segmentation of small organs in whole-body MRI is di...
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High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks
The ability to generate synthetic medical images is useful for data augm...
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Real-time Prediction of Segmentation Quality
Recent advances in deep learning based image segmentation methods have e...
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Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging
Recent advances in deep learning led to novel generative modeling techni...
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NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
NeuroNet is a deep convolutional neural network mimicking multiple popul...
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Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents
We propose a fully automatic method to find standardized view planes in ...
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Semi-Supervised Learning via Compact Latent Space Clustering
We present a novel cost function for semi-supervised learning of neural ...
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Nonparametric Density Flows for MRI Intensity Normalisation
With the adoption of powerful machine learning methods in medical image ...
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Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity
Graph convolutional networks (GCNs) allow to apply traditional convoluti...
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Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease
Graphs are widely used as a natural framework that captures interactions...
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Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy
The variations in multi-center data in medical imaging studies have brou...
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Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
Pose estimation, i.e. predicting a 3D rigid transformation with respect ...
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Attention-Gated Networks for Improving Ultrasound Scan Plane Detection
In this work, we apply an attention-gated network to real-time automated...
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Attention U-Net: Learning Where to Look for the Pancreas
We propose a novel attention gate (AG) model for medical imaging that au...
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Learning-Based Quality Control for Cardiac MR Images
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...
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DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images
We present DLTK, a toolkit providing baseline implementations for effici...
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Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
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Implicit Weight Uncertainty in Neural Networks
We interpret HyperNetworks within the framework of variational inference...
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Human-level CMR image analysis with deep fully convolutional networks
Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...
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3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images
Limited capture range and the requirement to provide high quality initia...
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Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
Incorporation of prior knowledge about organ shape and location is key t...
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Efficient variational Bayesian neural network ensembles for outlier detection
In this work we perform outlier detection using ensembles of neural netw...
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