James R. Clough
Orcid: 0000-0002-9135-0545Affiliations:
- King's College London, School of Biomedical Engineering and Imaging Sciences, UK (current)
- Imperial College London, Centre for Complexity Science, UK (former)
According to our database1,
James R. Clough
authored at least 34 papers
between 2014 and 2023.
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Bibliography
2023
A Persistent Homology-Based Topological Loss for CNN-Based Multiclass Segmentation of CMR.
IEEE Trans. Medical Imaging, 2023
2022
A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
2021
Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data.
IEEE J. Biomed. Health Informatics, 2021
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR.
CoRR, 2021
2020
Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation.
IEEE Trans. Medical Imaging, 2020
Weighted Manifold Alignment using Wave Kernel Signatures for Aligning Medical Image Datasets.
IEEE Trans. Pattern Anal. Mach. Intell., 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
A Persistent Homology-Based Topological Loss Function for Multi-class CNN Segmentation of Cardiac MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020
2019
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.
Medical Image Anal., 2019
CoRR, 2019
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space.
CoRR, 2019
High-quality segmentation of low quality cardiac MR images using k-space artefact correction.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019
Pseudo-normal PET Synthesis with Generative Adversarial Networks for Localising Hypometabolism in Epilepsies.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2019
Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 2019
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Image Reconstruction in a Manifold of Image Patches: Application to Whole-Fetus Ultrasound Imaging.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Topology-Preserving Augmentation for CNN-Based Segmentation of Congenital Heart Defects from 3D Paediatric CMR.
Proceedings of the Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis, 2019
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology.
Proceedings of the Information Processing in Medical Imaging, 2019
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2018
Automated CNN-Based Reconstruction of Short-Axis Cardiac MR Sequence from Real-Time Image Data.
Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018
Evaluation of Strategies for PET Motion Correction - Manifold Learning vs. Deep Learning.
Proceedings of the Understanding and Interpreting Machine Learning in Medical Image Computing Applications, 2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2017
2016
2015
Time & Citation Networks.
Proceedings of the 15th International Conference on Scientometrics and Informetrics, Istanbul, Turkey, June 29, 2015
2014