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FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation
In recent years, data-driven machine learning (ML) methods have revoluti...
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Personalized Federated Deep Learning for Pain Estimation From Face Images
Standard machine learning approaches require centralizing the users' dat...
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Privacy-preserving medical image analysis
The utilisation of artificial intelligence in medicine and healthcare ha...
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Reducing Textural Bias Improves Robustness of Deep Segmentation CNNs
Despite current advances in deep learning, domain shift remains a common...
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2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments
Federated Learning harnesses data from multiple sources to build a singl...
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A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification
This work provides a comprehensive review of existing frameworks based o...
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Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging
Deep neural networks exhibit limited generalizability across images with...
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Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
Federated learning (FL) has enabled training models collaboratively from...
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Efficient, high-performance pancreatic segmentation using multi-scale feature extraction
For artificial intelligence-based image analysis methods to reach clinic...
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Patch-based Brain Age Estimation from MR Images
Brain age estimation from Magnetic Resonance Images (MRI) derives the di...
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Causal Future Prediction in a Minkowski Space-Time
Estimating future events is a difficult task. Unlike humans, machine lea...
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Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment
Learning deep neural networks that are generalizable across different do...
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Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images
Accurate detection of anatomical landmarks is an essential step in sever...
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Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening
Prenatal screening with ultrasound can lower neonatal mortality signific...
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Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface
Accurate estimation of the age in neonates is essential for measuring ne...
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Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction
We present a deep network interpolation strategy for accelerated paralle...
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3D Probabilistic Segmentation and Volumetry from 2D projection images
X-Ray imaging is quick, cheap and useful for front-line care assessment ...
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Ultrasound Video Summarization using Deep Reinforcement Learning
Video is an essential imaging modality for diagnostics, e.g. in ultrasou...
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Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation
This paper proposes a fully automated atlas-based pancreas segmentation ...
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Learning Cross-domain Generalizable Features by Representation Disentanglement
Deep learning models exhibit limited generalizability across different d...
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Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction
Purpose: To systematically investigate the influence of various data con...
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Deep learning for cardiac image segmentation: A review
Deep learning has become the most widely used approach for cardiac image...
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Joint analysis of clinical risk factors and 4D cardiac motion for survival prediction using a hybrid deep learning network
In this work, a novel approach is proposed for joint analysis of high di...
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Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction
We present simple reconstruction networks for multi-coil data by extendi...
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Intelligent image synthesis to attack a segmentation CNN using adversarial learning
Deep learning approaches based on convolutional neural networks (CNNs) h...
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dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
AUTOMAP is a promising generalized reconstruction approach, however, it ...
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Model-Based and Data-Driven Strategies in Medical Image Computing
Model-based approaches for image reconstruction, analysis and interpreta...
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Flexible Conditional Image Generation of Missing Data with Learned Mental Maps
Real-world settings often do not allow acquisition of high-resolution vo...
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Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound
One of the biggest challenges for deep learning algorithms in medical im...
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Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image
Accelerating the acquisition of magnetic resonance imaging (MRI) is a ch...
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Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
In this work, we present a fully automatic method to segment cardiac str...
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Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders
Maintaining good cardiac function for as long as possible is a major con...
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Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images
Cardiac MR image segmentation is essential for the morphological and fun...
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k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
Dynamic magnetic resonance imaging (MRI) exhibits high correlations in k...
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VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
In this work, we propose a deep learning approach for parallel magnetic ...
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Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation
Deep learning models trained on medical images from a source domain (e.g...
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Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
In the recent years, convolutional neural networks have transformed the ...
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Multiple Landmark Detection using Multi-Agent Reinforcement Learning
The detection of anatomical landmarks is a vital step for medical image ...
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Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling
Quantification of anatomical shape changes still relies on scalar global...
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Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space
In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corru...
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Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes
We introduce a novel personalized Gaussian Process Experts (pGPE) model ...
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Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations
We propose a fully unsupervised multi-modal deformable image registratio...
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3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders
Accurate segmentation of heart structures imaged by cardiac MR is key fo...
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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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Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review
The medical image analysis field has traditionally been focused on the d...
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GANsfer Learning: Combining labelled and unlabelled data for GAN based data augmentation
Medical imaging is a domain which suffers from a paucity of manually ann...
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Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging
Detecting acoustic shadows in ultrasound images is important in many cli...
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A generic framework for privacy preserving deep learning
We detail a new framework for privacy preserving deep learning and discu...
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Multi-Task Learning for Left Atrial Segmentation on GE-MRI
Segmentation of the left atrium (LA) is crucial for assessing its anatom...
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Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning
Good quality of medical images is a prerequisite for the success of subs...
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