30 citations · 104 across the 10 of their papers we have counts for
5 papers · 1 filter
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
Wenjia Bai, Chen Chen, Giacomo Tarroni +6
In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety o…
Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography
Wenqi Lu, Jinming Duan, David Orive-Miguel +2
Total variation (TV) is a powerful regularization method that has been widely applied in different imaging applications, but is difficult to apply to diffuse optical tomography (DO…
OCT segmentation: Integrating open parametric contour model of the retinal layers and shape constraint to the Mumford-Shah functional
Jinming Duan, Weicheng Xie, Ryan Wen Liu +4
In this paper, we propose a novel retinal layer boundary model for segmentation of optical coherence tomography (OCT) images. The retinal layer boundary model consists of 9 open pa…
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach
Jinming Duan, Ghalib Bello, Jo Schlemper +7
Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image…
Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension
Jinming Duan, Jo Schlemper, Wenjia Bai +6
In this paper we introduce a novel and accurate optimisation method for segmentation of cardiac MR (CMR) images in patients with pulmonary hypertension (PH). The proposed method ex…