b'Wenjia Bai'

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 ...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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 ...

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 ...

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...

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...

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...

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...

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...

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...

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 ...

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...

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...

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...

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 ...

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...

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...

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...

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...

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...

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...

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...

Martin Rajchl, et al. ∙

Wenjia Bai

Featured Co-authors