Konstantinos Kamnitsas

发表

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

Loïc Le Folgoc, Daniel C. Castro, Jeremy Tan, 2019, IPMI.

Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning: Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings

Konstantinos Kamnitsas, Shadi Albarqouni, Spyridon Bakas, 2020, DART/DCL@MICCAI.

Towards continual learning in medical imaging pdf

Konstantinos Kamnitsas, Ben Glocker, Chaitanya Baweja, 2018, ArXiv.

Semi-Supervised Learning via Compact Latent Space Clustering pdf

Loïc Le Folgoc, Daniel C. Castro, Konstantinos Kamnitsas, 2018, ICML.

Domain Generalization via Model-Agnostic Learning of Semantic Features

Daniel C. Castro, Konstantinos Kamnitsas, Qi Dou, 2019, NeurIPS.

TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation

Konstantinos Kamnitsas, Daniel Rueckert, Steven McDonagh, 2019, BrainLes@MICCAI.

Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2018 .

Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2017, IEEE Transactions on Medical Imaging.

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound

Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz, 2016, IEEE Transactions on Medical Imaging.

Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network

Konstantinos Kamnitsas, Daniel Rueckert, Jennifer Keegan, 2016, 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS).

Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging

Konstantinos Kamnitsas, Amir Alansary, Steven McDonagh, 2017, CMMI/RAMBO/SWITCH@MICCAI.

Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling

Konstantinos Kamnitsas, Daniel Rueckert, Juan J. Cerrolaza, 2019, ArXiv.

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty pdf

Konstantinos Kamnitsas, Mark van der Wilk, Nick Pawlowski, 2020, NeurIPS.

Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation

Konstantinos Kamnitsas, Daniel Rueckert, Jinming Duan, 2019, MICCAI.

Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound pdf

Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz, 2016, ArXiv.

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks

Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz, 2016, IEEE Transactions on Medical Imaging.

Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation pdf

Konstantinos Kamnitsas, Ben Glocker, Zeju Li, 2019, MICCAI.

Deep learning: Generative adversarial networks and adversarial methods

Konstantinos Kamnitsas, Christian Ledig, Jelmer M. Wolterink, 2019 .

Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks

Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz, 2016, MICCAI.

Autofocus Layer for Semantic Segmentation

Konstantinos Kamnitsas, Garrison W. Cottrell, Antonio Criminisi, 2018, MICCAI.

Segmentation of Traumatic Brain Injuries with Convolutional Neural Networks

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2015 .

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2017, BrainLes@MICCAI.

Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

Loïc Le Folgoc, Konstantinos Kamnitsas, Amir Alansary, 2018, MICCAI.

Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI

Konstantinos Kamnitsas, Amir Alansary, Ben Glocker, 2016, MICCAI.

Generative adversarial networks and adversarial methods in biomedical image analysis pdf

Konstantinos Kamnitsas, Christian Ledig, Jelmer M. Wolterink, 2018, ArXiv.

Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2015 .

Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks

Konstantinos Kamnitsas, Daniel Rueckert, Declan P. O'Regan, 2016, MICCAI.

Evaluating reinforcement learning agents for anatomical landmark detection

Loïc Le Folgoc, Konstantinos Kamnitsas, Amir Alansary, 2019, Medical Image Anal..

A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling

Konstantinos Kamnitsas, Daniel Rueckert, Mary A. Rutherford, 2020, MIDL.

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data

Joseph Ross Mitchell, Konstantinos Kamnitsas, Leland S. Hu, 2020, Journal of medical imaging.

Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy pdf

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2018, ArXiv.

Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2017, IEEE Transactions on Medical Imaging.

Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2016, Medical Image Anal..

Multiple Landmark Detection using Multi-Agent Reinforcement Learning

Konstantinos Kamnitsas, Amir Alansary, Daniel Rueckert, 2019, MICCAI.

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2016, IPMI.

DeepMedic for Brain Tumor Segmentation

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2016, BrainLes@MICCAI.

Analyzing Overfitting Under Class Imbalance in Neural Networks for Image Segmentation

Konstantinos Kamnitsas, Ben Glocker, Zeju Li, 2020, IEEE Transactions on Medical Imaging.

Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation

Konstantinos Kamnitsas, Ben Glocker, James H. Cole, 2021, IPMI.

Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis

Konstantinos Kamnitsas, Ben Glocker, Magdalini Paschali, 2021, UNSURE/PIPPI@MICCAI.

Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift

Konstantinos Kamnitsas, Ben Glocker, Gregory Filbrandt, 2021, DART/FAIR@MICCAI.

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

Konstantinos Kamnitsas, Ben Glocker, Daniel Rueckert, 2021, DART/FAIR@MICCAI.

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty pdf

Konstantinos Kamnitsas, Mark van der Wilk, Nick Pawlowski, 2020, NeurIPS.

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

Jean-Philippe Thiran, Konstantinos Kamnitsas, Ben Glocker, 2017, PloS one.