200 citations · 476 across the 18 of their papers we have counts for
8 papers · 1 filter
Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography
Alberto Gomez, Mihaela Porumb, Angela Mumith +5
We propose a new method to automatically contour the left ventricle on 2D echocardiographic images. Unlike most existing segmentation methods, which are based on predicting segment…
CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation
Thierry Judge, Olivier Bernard, Mihaela Porumb +3
Accurate uncertainty estimation is a critical need for the medical imaging community. A variety of methods have been proposed, all direct extensions of classification uncertainty e…
Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling
Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias +1
Automatic segmentation of multi-sequence (multi-modal) cardiac MR (CMR) images plays a significant role in diagnosis and management for a variety of cardiac diseases. However, the…
Semi-supervised Pathology Segmentation with Disentangled Representations
Haochuan Jiang, Agisilaos Chartsias, Xinheng Zhang +6
Automated pathology segmentation remains a valuable diagnostic tool in clinical practice. However, collecting training data is challenging. Semi-supervised approaches by combining…
Disentangled Representations for Domain-generalized Cardiac Segmentation
Xiao Liu, Spyridon Thermos, Agisilaos Chartsias +2
Robust cardiac image segmentation is still an open challenge due to the inability of the existing methods to achieve satisfactory performance on unseen data of different domains. S…
Pseudo-healthy synthesis with pathology disentanglement and adversarial learning
Tian Xia, Agisilaos Chartsias, Sotirios A. Tsaftaris
Pseudo-healthy synthesis is the task of creating a subject-specific `healthy' image from a pathological one. Such images can be helpful in tasks such as anomaly detection and under…
Learning to synthesise the ageing brain without longitudinal data
Tian Xia, Agisilaos Chartsias, Chengjia Wang +1
How will my face look when I get older? Or, for a more challenging question: How will my brain look when I get older? To answer this question one must devise (and learn from data)…
Conditioning Convolutional Segmentation Architectures with Non-Imaging Data
Grzegorz Jacenków, Agisilaos Chartsias, Brian Mohr +1
We compare two conditioning mechanisms based on concatenation and feature-wise modulation to integrate non-imaging information into convolutional neural networks for segmentation o…