271 citations · 549 across the 18 of their papers we have counts for
9 papers · 1 filter
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
Nick Byrne, James R Clough, Isra Valverde +2
Multi-class segmentation of cardiac magnetic resonance (CMR) images seeks a separation of data into anatomical components with known structure and configuration. The most popular C…
A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI
Nick Byrne, James R. Clough, Giovanni Montana +1
With respect to spatial overlap, CNN-based segmentation of short axis cardiovascular magnetic resonance (CMR) images has achieved a level of performance consistent with inter obser…
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction
Esther Puyol-Antón, Chen Chen, James R. Clough +9
Advances in deep learning (DL) have resulted in impressive accuracy in some medical image classification tasks, but often deep models lack interpretability. The ability of these mo…
Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation
Ilkay Oksuz, James R. Clough, Bram Ruijsink +6
Segmenting anatomical structures in medical images has been successfully addressed with deep learning methods for a range of applications. However, this success is heavily dependen…
Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging
Tong Zhang, Laurence H. Jackson, Alena Uus +5
Accurately estimating and correcting the motion artifacts are crucial for 3D image reconstruction of the abdominal and in-utero magnetic resonance imaging (MRI). The state-of-art m…
Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR
Nick Byrne, James R. Clough, Isra Valverde +2
Patient-specific 3D printing of congenital heart anatomy demands an accurate segmentation of the thin tissue interfaces which characterise these diagnoses. Even when a label set ha…
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space
lkay Oksuz, James Clough, Bram Ruijsink +7
In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corruption of k-space lines, which can result in artefacts in the reconstructed images. In this paper, we propose…
Global and Local Interpretability for Cardiac MRI Classification
James R. Clough, Ilkay Oksuz, Esther Puyol-Anton +3
Deep learning methods for classifying medical images have demonstrated impressive accuracy in a wide range of tasks but often these models are hard to interpret, limiting their app…
Mechanically Powered Motion Imaging Phantoms: Proof of Concept
Alberto Gomez, Cornelia Schmitz, Markus Henningsson +8
Motion imaging phantoms are expensive, bulky and difficult to transport and set-up. The purpose of this paper is to demonstrate a simple approach to the design of multi-modality mo…