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09/04/2023
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
Implementing neural networks for clinical use in medical applications ne...
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08/31/2023
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment
Deployment of Deep Neural Networks in medical imaging is hindered by dis...
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08/30/2023
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Unsupervised anomaly segmentation aims to detect patterns that are disti...
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05/30/2023
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation
This paper presents an effective and general data augmentation framework...
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06/27/2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
Machine learning models deployed on medical imaging tasks must be equipp...
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07/19/2021
Transductive image segmentation: Self-training and effect of uncertainty estimation
Semi-supervised learning (SSL) uses unlabeled data during training to le...
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07/13/2021
Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift
Scarcity of high quality annotated images remains a limiting factor for ...
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07/06/2021
Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis
Image classification models deployed in the real world may receive input...
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04/28/2021
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation
We propose a parameter efficient Bayesian layer for hierarchical convolu...
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02/20/2021
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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06/10/2020
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
In image segmentation, there is often more than one plausible solution f...
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10/29/2019
Domain Generalization via Model-Agnostic Learning of Semantic Features
Generalization capability to unseen domains is crucial for machine learn...
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07/25/2019
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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07/05/2019
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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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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06/28/2019
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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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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11/06/2018
Towards continual learning in medical imaging
This work investigates continual learning of two segmentation tasks in b...
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10/24/2018
Generative adversarial networks and adversarial methods in biomedical image analysis
Generative adversarial networks (GANs) and other adversarial methods are...
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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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06/07/2018
Semi-Supervised Learning via Compact Latent Space Clustering
We present a novel cost function for semi-supervised learning of neural ...
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06/01/2018
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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05/22/2018
Autofocus Layer for Semantic Segmentation
We propose the autofocus convolutional layer for semantic segmentation w...
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11/04/2017
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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05/22/2017
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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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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12/28/2016
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Significant advances have been made towards building accurate automatic ...
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12/16/2016
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound
Identifying and interpreting fetal standard scan planes during 2D ultras...
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05/25/2016
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks
In this paper, we propose DeepCut, a method to obtain pixelwise object s...
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03/18/2016