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Featured Co-authors

Daniel Rueckert
199 publications
Shuo Wang
101 publications
Ben Glocker
95 publications
Yike Guo
67 publications
Chen Chen
59 publications
Bernhard Kainz
46 publications
Yuan Wang
46 publications
Andrew P. King
37 publications
Konstantinos Kamnitsas
30 publications
Jinming Duan
30 publications
Yi Guo
29 publications

research

∙ 08/16/2023

Hierarchical Uncertainty Estimation for Medical Image Segmentation Networks

Learning a medical image segmentation model is an inherently ambiguous t...

0 Xinyu Bai, et al. ∙

research

∙ 01/30/2023

CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy

Two key questions in cardiac image analysis are to assess the anatomy an...

0 Mengyun Qiao, et al. ∙

research

∙ 09/05/2022

Mesh-based 3D Motion Tracking in Cardiac MRI using Deep Learning

3D motion estimation from cine cardiac magnetic resonance (CMR) images i...

0 Qingjie Meng, et al. ∙

research

∙ 08/28/2022

Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data

Cardiovascular disease, the leading cause of death globally, is an age-r...

10 Mengyun Qiao, et al. ∙

research

∙ 08/03/2022

Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

Understanding the intensity characteristics of brain lesions is key for ...

0 Berke Doga Basaran, et al. ∙

research

∙ 07/29/2022

MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI

Recovering the 3D motion of the heart from cine cardiac magnetic resonan...

7 Qingjie Meng, et al. ∙

research

∙ 06/02/2022

Suggestive Annotation of Brain MR Images with Gradient-guided Sampling

Machine learning has been widely adopted for medical image analysis in r...

0 Chengliang Dai, et al. ∙

research

∙ 05/31/2022

Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images

In recent years, 3D convolutional neural networks have become the domina...

0 Yuan Wang, et al. ∙

research

∙ 09/30/2021

DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization

In recent years, the research landscape of machine learning in medical i...

51 Turkay Kart, et al. ∙

research

∙ 07/16/2021

Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation

Optimising the analysis of cardiac structure and function requires accur...

5 Nicolo' Savioli, et al. ∙

research

∙ 06/26/2020

Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling

Machine learning has been widely adopted for medical image analysis in r...

0 Chengliang Dai, et al. ∙

research

∙ 11/19/2019

Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction

Gliomas are the most common malignant brain tumourswith intrinsic hetero...

0 Shuo Wang, et al. ∙

research

∙ 11/09/2019

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image...

95 Chen Chen, et al. ∙

research

∙ 08/28/2019

Transfer Learning from Partial Annotations for Whole Brain Segmentation

Brain MR image segmentation is a key task in neuroimaging studies. It is...

0 Chengliang Dai, et al. ∙

research

∙ 08/20/2019

Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image

Accelerating the acquisition of magnetic resonance imaging (MRI) is a ch...

4 Chen Qin, et al. ∙

research

∙ 08/20/2019

Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation

In this work, we present a fully automatic method to segment cardiac str...

0 Chen Chen, et al. ∙

research

∙ 07/23/2019

Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images

Cardiac MR image segmentation is essential for the morphological and fun...

5 Chen Chen, et al. ∙

research

∙ 07/19/2019

VS-Net: Variable splitting network for accelerated parallel MRI reconstruction

In this work, we propose a deep learning approach for parallel magnetic ...

2 Jinming Duan, et al. ∙

research

∙ 07/05/2019

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

In the recent years, convolutional neural networks have transformed the ...

6 Wenjia Bai, 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

∙ 01/27/2019

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...

38 Robert Robinson, et al. ∙

research

∙ 10/31/2018

Multi-Task Learning for Left Atrial Segmentation on GE-MRI

Segmentation of the left atrium (LA) is crucial for assessing its anatom...

4 Chen Chen, et al. ∙

research

∙ 10/03/2018

A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

In the clinical routine, short axis (SA) cine cardiac MR (CMR) image sta...

8 Giacomo Tarroni, et al. ∙

research

∙ 08/26/2018

Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach

Deep learning approaches have achieved state-of-the-art performance in c...

0 Jinming Duan, et al. ∙

research

∙ 08/01/2018

Recurrent neural networks for aortic image sequence segmentation with sparse annotations

Segmentation of image sequences is an important task in medical image an...

6 Wenjia Bai, et al. ∙

research

∙ 07/27/2018

Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension

In this paper we introduce a novel and accurate optimisation method for ...

12 Jinming Duan, et al. ∙

research

∙ 07/18/2018

Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling

Alterations in the geometry and function of the heart define well-establ...

8 Carlo Biffi, et al. ∙

research

∙ 06/16/2018

Real-time Prediction of Segmentation Quality

Recent advances in deep learning based image segmentation methods have e...

14 Robert Robinson, et al. ∙

research

∙ 06/11/2018

Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences

Cardiac motion estimation and segmentation play important roles in quant...

0 Chen Qin, 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

∙ 06/01/2018

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

∙ 04/24/2018

Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks

Measurement of head biometrics from fetal ultrasonography images is of k...

6 Matthew Sinclair, et al. ∙

research

∙ 03/25/2018

Learning-Based Quality Control for Cardiac MR Images

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...

0 Giacomo Tarroni, 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

∙ 10/25/2017

Human-level CMR image analysis with deep fully convolutional networks

Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...

0 Wenjia Bai, 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

∙ 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. ∙

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