Konstantinos Kamnitsas

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Daniel Rueckert
199 publications
Qi Dou
97 publications
Ben Glocker
95 publications
Bernhard Kainz
46 publications
Mark van der Wilk
44 publications
Wenjia Bai
37 publications
Ivana Isgum
35 publications
Jelmer M. Wolterink
34 publications
Jinming Duan
30 publications
Enzo Ferrante
27 publications
Steven McDonagh
27 publications

research

∙ 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...

0 Harry Anthony, et al. ∙

research

∙ 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...

0 Felix Wagner, et al. ∙

research

∙ 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...

0 Ziyun Liang, et al. ∙

research

∙ 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...

0 Zeju Li, et al. ∙

research

∙ 06/27/2022

Distributional Gaussian Processes Layers for Out-of-Distribution Detection

Machine learning models deployed on medical imaging tasks must be equipp...

18 Sebastian G. Popescu, et al. ∙

research

∙ 07/19/2021

Transductive image segmentation: Self-training and effect of uncertainty estimation

Semi-supervised learning (SSL) uses unlabeled data during training to le...

11 Konstantinos Kamnitsas, et al. ∙

research

∙ 07/13/2021

Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift

Scarcity of high quality annotated images remains a limiting factor for ...

3 Gregory Filbrandt, et al. ∙

research

∙ 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...

8 Christoph Berger, et al. ∙

research

∙ 04/28/2021

Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation

We propose a parameter efficient Bayesian layer for hierarchical convolu...

25 Sebastian G. Popescu, et al. ∙

research

∙ 02/20/2021

Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation

Class imbalance poses a challenge for developing unbiased, accurate pred...

7 Zeju Li, et al. ∙

research

∙ 06/10/2020

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

In image segmentation, there is often more than one plausible solution f...

32 Miguel Monteiro, et al. ∙

research

∙ 10/29/2019

Domain Generalization via Model-Agnostic Learning of Semantic Features

Generalization capability to unseen domains is crucial for machine learn...

21 Qi Dou, et al. ∙

research

∙ 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...

6 Zeju Li, et al. ∙

research

∙ 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...

7 Cheng Ouyang, et al. ∙

research

∙ 06/30/2019

Multiple Landmark Detection using Multi-Agent Reinforcement Learning

The detection of anatomical landmarks is a vital step for medical image ...

3 Athanasios Vlontzos, et al. ∙

research

∙ 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...

1 Carlo Biffi, et al. ∙

research

∙ 03/06/2019

Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing

We investigate discrete spin transformations, a geometric framework to m...

0 Loic Le Folgoc, et al. ∙

research

∙ 11/06/2018

Towards continual learning in medical imaging

This work investigates continual learning of two segmentation tasks in b...

16 Chaitanya Baweja, et al. ∙

research

∙ 10/24/2018

Generative adversarial networks and adversarial methods in biomedical image analysis

Generative adversarial networks (GANs) and other adversarial methods are...

4 Jelmer M. Wolterink, et al. ∙

research

∙ 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 ...

10 Amir Alansary, et al. ∙

research

∙ 06/07/2018

Semi-Supervised Learning via Compact Latent Space Clustering

We present a novel cost function for semi-supervised learning of neural ...

2 Konstantinos Kamnitsas, et al. ∙

research

∙ 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...

0 Vanya V. Valindria, et al. ∙

research

∙ 05/22/2018

Autofocus Layer for Semantic Segmentation

We propose the autofocus convolutional layer for semantic segmentation w...

0 Yao Qin, et al. ∙

research

∙ 11/04/2017

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Deep learning approaches such as convolutional neural nets have consiste...

0 Konstantinos Kamnitsas, et al. ∙

research

∙ 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...

0 Ozan Oktay, et al. ∙

research

∙ 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...

0 Steven McDonagh, et al. ∙

research

∙ 12/28/2016

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Significant advances have been made towards building accurate automatic ...

0 Konstantinos Kamnitsas, et al. ∙

research

∙ 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...

0 Christian F. Baumgartner, et al. ∙

research

∙ 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...

0 Martin Rajchl, et al. ∙

research

∙ 03/18/2016

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

We propose a dual pathway, 11-layers deep, three-dimensional Convolution...

0 Konstantinos Kamnitsas, et al. ∙

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