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02/27/2022
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption
This work presents a novel protocol for fast secure inference of neural ...
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12/02/2021
FedRAD: Federated Robust Adaptive Distillation
The robustness of federated learning (FL) is vital for the distributed t...
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07/31/2021
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
Datasets are rarely a realistic approximation of the target population. ...
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09/17/2020
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
Federated learning (FL) has enabled training models collaboratively from...
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08/18/2020
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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08/13/2020
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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08/29/2019
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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06/30/2019
Multiple Landmark Detection using Multi-Agent Reinforcement Learning
The detection of anatomical landmarks is a vital step for medical image ...
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03/06/2019
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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06/19/2018
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network
Standard scan plane detection in fetal brain ultrasound (US) forms a cru...
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06/18/2018
Fast Multiple Landmark Localisation Using a Patch-based Iterative Network
We propose a new Patch-based Iterative Network (PIN) for fast and accura...
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06/08/2018
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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05/02/2018
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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09/19/2017
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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02/28/2017
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging
3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast bu...
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02/28/2017
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion
This paper aims to solve a fundamental problem in intensity-based 2D/3D ...
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11/22/2016
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
In this paper we present a novel method for the correction of motion art...
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06/03/2016