Showing 50 publications by Abhirup Banerjee
Identifying extra pulmonary vein targets for persistent atrial fibrillation ablation: bridging advanced and conventional mapping techniques
Sharp AJ, Pope MT, Briosa e Gala A, Varini R, Banerjee A et al. (2025), EP Europace, 27(4)
BibTeX
@article{identifyingextr-2025/3,
title={Identifying extra pulmonary vein targets for persistent atrial fibrillation ablation: bridging advanced and conventional mapping techniques},
author={Sharp AJ, Pope MT, Briosa e Gala A, Varini R, Banerjee A et al.},
journal={EP Europace},
volume={27},
number={euaf048},
publisher={Oxford University Press},
year = "2025"
}
New trends of adversarial machine learning for data fusion and intelligent system
Ding W, Zhang Z, Martínez L, Huang Y, Cao Z et al. (2025), Information Fusion, 114, 102683
Deep learning based coronary vessels segmentation in X-ray angiography using temporal information
He H, Banerjee A, Choudhury RP & Grau V (2025), Medical Image Analysis, 103496-103496
BibTeX
@article{deeplearningbas-2025/2,
title={Deep learning based coronary vessels segmentation in X-ray angiography using temporal information},
author={He H, Banerjee A, Choudhury RP & Grau V},
journal={Medical Image Analysis},
number={103496},
pages={103496-103496},
publisher={Elsevier BV},
year = "2025"
}
Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation.
Sharp AJ, Pope MTB, Briosa E Gala A, Varini R, Betts TR et al. (2025), Royal Society open science, 12(1), 241048
BibTeX
@article{multimodalinteg-2025/1,
title={Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation.},
author={Sharp AJ, Pope MTB, Briosa E Gala A, Varini R, Betts TR et al.},
journal={Royal Society open science},
volume={12},
pages={241048},
publisher={The Royal Society},
year = "2025"
}
Personalized topology-informed localization of standard 12-lead ECG electrode placement from incomplete cardiac MRIs for efficient cardiac digital twins.
Li L, Smith H, Lyu Y, Camps J, Qian S et al. (2025), Medical image analysis, 101, 103472
BibTeX
@article{personalizedtop-2025/1,
title={Personalized topology-informed localization of standard 12-lead ECG electrode placement from incomplete cardiac MRIs for efficient cardiac digital twins.},
author={Li L, Smith H, Lyu Y, Camps J, Qian S et al.},
journal={Medical image analysis},
volume={101},
number={103472},
pages={103472},
publisher={Elsevier},
year = "2025"
}
Editorial: Artificial intelligence applications for cancer diagnosis in radiology
Banerjee A, Shan H & Feng R (2025), Frontiers in Radiology, 5, 1493783
Self-supervised Instance Segmentation of Diabetic Foot Ulcers via Feature Correspondence Distillation
Zhang W, Banerjee A & Ray S (2025), 15335, 42-54
NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections via Neural Implicit Representation
Wang Y, Banerjee A & Grau V (2024), Bioengineering, 11(12), 1227-1227
Deep Learning-based Modelling of Complex Hypertensive Multi-Organ Damage with Uncertainty Quantification from Simple Clinical Measures
Kart T, Alkhodari M, Lapidaire W, Banerjee A, Lewandowski AJ et al. (2024), 00, 1542-1547
BibTeX
@inproceedings{deeplearningbas-2024/12,
title={Deep Learning-based Modelling of Complex Hypertensive Multi-Organ Damage with Uncertainty Quantification from Simple Clinical Measures},
author={Kart T, Alkhodari M, Lapidaire W, Banerjee A, Lewandowski AJ et al.},
booktitle={2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
pages={1542-1547},
year = "2024"
}
Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation
Sharp AJ, Pope MTB, Gala ABE, Varini R, Betts TR et al. (2024), European Heart Journal, 45(Supplement_1), ehae666.439
BibTeX
@article{impactofadjacen-2024/10,
title={Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation},
author={Sharp AJ, Pope MTB, Gala ABE, Varini R, Betts TR et al.},
journal={European Heart Journal},
volume={45},
pages={ehae666.439},
publisher={Oxford University Press (OUP)},
year = "2024"
}
Comprehensive cardiac interval analysis in the WEAR-TECH study cohort by comparing the Apple Watch Series 6 against a simultaneous 12-lead ECG
Schramm D, Varini R, Gala ABE, Banerjee A & Betts T (2024), European Heart Journal, 45(Supplement_1), ehae666.353
BibTeX
@article{comprehensiveca-2024/10,
title={Comprehensive cardiac interval analysis in the WEAR-TECH study cohort by comparing the Apple Watch Series 6 against a simultaneous 12-lead ECG},
author={Schramm D, Varini R, Gala ABE, Banerjee A & Betts T},
journal={European Heart Journal},
volume={45},
pages={ehae666.353},
publisher={Oxford University Press (OUP)},
year = "2024"
}
“Real‐world” performance of the Confirm Rx™ SharpSense AF detection algorithm: UK Confirm Rx study
Briosa e Gala A, Pope MTB, Leo M, Sharp AJ, Banerjee A et al. (2024), Journal of Arrhythmia
NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections via Neural Implicit Representation
Wang Y, Banerjee A & Grau V (2024)
Modeling the mechanisms of non-neurogenic dynamic cerebral autoregulation
van Zijl N, Banerjee A & Payne SJ (2024), IEEE Transactions on Biomedical Engineering, 72(2), 577-585
Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.
Beetz M, Banerjee A & Grau V (2024), IEEE journal of biomedical and health informatics, 28(8), 4810-4819
Role of impedance drop and lesion size index (LSI) to guide catheter ablation for atrial fibrillation
Leo M, Banerjee A, Gala ABE, Pope M, Pedersen M et al. (2024), Pacing and Clinical Electrophysiology
Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning
Mamalakis M, Banerjee A, Ray S, Wilkie C, Clayton RH et al. (2024), Neural Computing and Applications, 1-22
BibTeX
@article{deepmultimetric-2024/8,
title={Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning},
author={Mamalakis M, Banerjee A, Ray S, Wilkie C, Clayton RH et al.},
journal={Neural Computing and Applications},
pages={1-22},
publisher={Springer Nature},
year = "2024"
}
Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories
Lashgari M, Choudhury RP & Banerjee A (2024), Frontiers in Cardiovascular Medicine, 11
BibTeX
@article{patientspecific-2024/7,
title={Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories},
author={Lashgari M, Choudhury RP & Banerjee A},
journal={Frontiers in Cardiovascular Medicine},
volume={11},
number={1398290},
publisher={Frontiers Media},
year = "2024"
}
DeepCA: Deep Learning-based 3D Coronary Artery Tree Reconstruction from Two 2D Non-simultaneous X-ray Angiography Projections
Wang Y, Banerjee A, Choudhury RP & Grau V (2024)
BibTeX
@misc{deepcadeeplearn-2024/7,
title={DeepCA: Deep Learning-based 3D Coronary Artery Tree Reconstruction from
Two 2D Non-simultaneous X-ray Angiography Projections},
author={Wang Y, Banerjee A, Choudhury RP & Grau V},
year = "2024"
}
Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review
Sharp AJ, Betts TR & Banerjee A (2024), Journal of Clinical Medicine, 13(15)
Cardiovascular magnetic resonance before invasive coronary angiography in suspected non-ST-segment elevation myocardial infarction
Shanmuganathan M, Nikolaidou C, Burrage M, Borlotti A, Kotronias R et al. (2024), JACC: Cardiovascular Imaging, 17(9), 1044-1058
BibTeX
@article{cardiovascularm-2024/6,
title={Cardiovascular magnetic resonance before invasive coronary angiography in suspected non-ST-segment elevation myocardial infarction},
author={Shanmuganathan M, Nikolaidou C, Burrage M, Borlotti A, Kotronias R et al.},
journal={JACC: Cardiovascular Imaging},
volume={17},
pages={1044-1058},
publisher={Elsevier},
year = "2024"
}
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.
Nan Y, Xing X, Wang S, Tang Z, Felder FN et al. (2024), Medical image analysis, 97, 103253
Uncertainty Quantification in Deep Learning Framework for Mallampati Classification
Mahato A, Sarangi P, Kurmi VK, Banerjee A, Goyal A et al. (2024), 00, 626-631
BibTeX
@inproceedings{uncertaintyquan-2024/6,
title={Uncertainty Quantification in Deep Learning Framework for Mallampati Classification},
author={Mahato A, Sarangi P, Kurmi VK, Banerjee A, Goyal A et al.},
booktitle={2024 IEEE 12th International Conference on Healthcare Informatics (ICHI)},
pages={626-631},
year = "2024"
}
TCPNet: A Novel Tumor Contour Prediction Network Using MRIs
Agarwal S, Kurmi VK, Banerjee A & Basu T (2024), 00, 183-188
Conduction velocity-based functional substrate mapping during atrial fibrillation (AF) enhances identification of AF drivers compared to mapping during sinus rhythm
Sharp AJ, Pope MTB, Gala A, Varini R, Banerjee A et al. (2024), EP Europace, 26(Supplement_1), euae102.135
BibTeX
@article{conductionveloc-2024/5,
title={Conduction velocity-based functional substrate mapping during atrial fibrillation (AF) enhances identification of AF drivers compared to mapping during sinus rhythm},
author={Sharp AJ, Pope MTB, Gala A, Varini R, Banerjee A et al.},
journal={EP Europace},
volume={26},
pages={euae102.135},
publisher={Oxford University Press (OUP)},
year = "2024"
}
Automated continuous rhythm monitoring with implantable cardiac monitor and real-time smartphone alerts during af episodes: SMART-ALERT study
Gala ABE, Pope M, Leo M, Sharp A, Varini R et al. (2024), EP Europace, 26(Supplement_1), euae102.230-euae102.230
BibTeX
@article{automatedcontin-2024/5,
title={Automated continuous rhythm monitoring with implantable cardiac monitor and real-time smartphone alerts during af episodes: SMART-ALERT study},
author={Gala ABE, Pope M, Leo M, Sharp A, Varini R et al.},
journal={EP Europace},
volume={26},
pages={euae102.230-euae102.230},
publisher={Oxford University Press (OUP)},
year = "2024"
}
Modelling Multi-Phase Cardiac Anatomy Using Point Cloud Variational Autoencoders
Seale T, Beetz M, Rodriguez B, Grau V & Banerjee A (2024), 00, 1-5
BibTeX
@inproceedings{modellingmultip-2024/5,
title={Modelling Multi-Phase Cardiac Anatomy Using Point Cloud Variational Autoencoders},
author={Seale T, Beetz M, Rodriguez B, Grau V & Banerjee A},
booktitle={2024 IEEE International Symposium on Biomedical Imaging (ISBI)},
pages={1-5},
year = "2024"
}
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Xu W, Moffat M, Seale T, Liang Z, Wagner F et al. (2024)
PO-03-143 SUPERIORITY OF FUNCTIONAL VS STRUCTURAL ATRIAL SUBSTRATE MAPPING FOR IDENTIFICATION OF NON-PULMONARY VEIN DRIVERS IN ATRIAL FIBRILLATION
Sharp AJ, Pope MT, Briosa e Gala A, Varini R, Banerjee A et al. (2024), Heart Rhythm, 21(5), s343-s344
BibTeX
@article{posuperiorityof-2024/5,
title={PO-03-143 SUPERIORITY OF FUNCTIONAL VS STRUCTURAL ATRIAL SUBSTRATE MAPPING FOR IDENTIFICATION OF NON-PULMONARY VEIN DRIVERS IN ATRIAL FIBRILLATION},
author={Sharp AJ, Pope MT, Briosa e Gala A, Varini R, Banerjee A et al.},
journal={Heart Rhythm},
volume={21},
pages={s343-s344},
publisher={Elsevier},
year = "2024"
}
Automated CMR index of left ventricular diastolic function post-acute myocardial infarction provides independent and incremental prediction of long-term prognosis when added to conventional indices
Shanmuganathan M, Gonzales Vera RA, Burrage M, Arvidsson P, Banerjee A et al. (2024), Proceedings of the CMR 2024 – The Global CMR Conference, 26(S1)
BibTeX
@inproceedings{automatedcmrind-2024/4,
title={Automated CMR index of left ventricular diastolic function post-acute myocardial infarction provides independent and incremental prediction of long-term prognosis when added to conventional indices},
author={Shanmuganathan M, Gonzales Vera RA, Burrage M, Arvidsson P, Banerjee A et al.},
booktitle={CMR 2024 – The Global CMR Conference},
year = "2024"
}
Scoring systems developed by machine learning: intelligent but simple to use?
Banerjee A & Leeson P (2024), European Heart Journal, 45(11), 937-939
Towards enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference
Li L, Camps J, Wang Z, Beetz M, Banerjee A et al. (2024), IEEE Transactions on Medical Imaging
BibTeX
@article{towardsenabling-2024/2,
title={Towards enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference},
author={Li L, Camps J, Wang Z, Beetz M, Banerjee A et al.},
journal={IEEE Transactions on Medical Imaging},
publisher={IEEE},
year = "2024"
}
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Xu W, Moffat M, Seale T, Liang Z, Wagner F et al. (2024), Proceedings of Machine Learning Research, 250, 1771-1784
BibTeX
@inproceedings{feasibilityandb-2024/1,
title={Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation},
author={Xu W, Moffat M, Seale T, Liang Z, Wagner F et al.},
pages={1771-1784},
year = "2024"
}
Automated Coronary Vessels Segmentation in X-ray Angiography Using Graph Attention Network
He H, Banerjee A, Choudhury RP & Grau V (2024), 14507, 209-219
Generating Virtual Populations of 3D Cardiac Anatomies with Snowflake-Net
Peng J, Beetz M, Banerjee A, Chen M & Grau V (2024), 14507, 163-173
CMR 2-47 Cardiovascular Magnetic Resonance Imaging Before Invasive Coronary Angiography in Suspected Non-st-segment Elevation Myocardial Infarction Can Change Management in over One-third of the Patients
Shanmuganathan M, Nikolaidou C, Burrage M, Borlotti A, Kotronias R et al. (2024), Journal of Cardiovascular Magnetic Resonance, 26, 100129
BibTeX
@article{cmrcardiovascul-2024/,
title={CMR 2-47 Cardiovascular Magnetic Resonance Imaging Before Invasive Coronary Angiography in Suspected Non-st-segment Elevation Myocardial Infarction Can Change Management in over One-third of the Patients},
author={Shanmuganathan M, Nikolaidou C, Burrage M, Borlotti A, Kotronias R et al.},
journal={Journal of Cardiovascular Magnetic Resonance},
volume={26},
pages={100129},
publisher={Elsevier},
year = "2024"
}
3D shape-based myocardial infarction prediction using point cloud classification networks
Beetz M, Yang Y, Banerjee A, Li L & Grau V (2023)
BibTeX
@inproceedings{dshapebasedmyoc-2023/12,
title={3D shape-based myocardial infarction prediction using point cloud classification networks},
author={Beetz M, Yang Y, Banerjee A, Li L & Grau V},
booktitle={45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023)},
year = "2023"
}
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images.
Beetz M, Banerjee A, Ossenberg-Engels J & Grau V (2023), Medical image analysis, 90, 102975
BibTeX
@article{multiclasspoint-2023/12,
title={Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images.},
author={Beetz M, Banerjee A, Ossenberg-Engels J & Grau V},
journal={Medical image analysis},
volume={90},
pages={102975},
year = "2023"
}
Anatomical basis of human sex differences in ECG identified by automated torso-cardiac three-dimensional reconstruction
Smith HJ, Rodriguez B, Sang Y, Beetz M, Choudhury R et al. (2023)
BibTeX
@misc{anatomicalbasis-2023/12,
title={Anatomical basis of human sex differences in ECG identified by automated
torso-cardiac three-dimensional reconstruction},
author={Smith HJ, Rodriguez B, Sang Y, Beetz M, Choudhury R et al.},
year = "2023"
}
HyperScore: A unified measure to model hypertension progression using multi-modality measurements and semi-supervised learning
Alkhodari M, Lapidaire W, Xiong Z, Kart T, Iturria-Medina Y et al. (2023), 00, 1886-1889
BibTeX
@inproceedings{hyperscoreaunif-2023/12,
title={HyperScore: A unified measure to model hypertension progression using multi-modality measurements and semi-supervised learning},
author={Alkhodari M, Lapidaire W, Xiong Z, Kart T, Iturria-Medina Y et al.},
booktitle={2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
pages={1886-1889},
year = "2023"
}
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Beetz M, Banerjee A, Ossenberg-Engels J & Grau V (2023), Medical Image Analysis, 90
BibTeX
@article{multiclasspoint-2023/9,
title={Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images},
author={Beetz M, Banerjee A, Ossenberg-Engels J & Grau V},
journal={Medical Image Analysis},
volume={90},
number={102975},
publisher={Elsevier},
year = "2023"
}
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks
Beetz M, Yang Y, Banerjee A, Li L & Grau V (2023)
Multi-objective point cloud autoencoders for explainable myocardial infarction prediction
Beetz M, Banerjee A & Grau V (2023)
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Beetz M, Banerjee A & Grau V (2023)
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Beetz M, Banerjee A, Ossenberg-Engels J & Grau V (2023)
Calcium dysregulation combined with mitochondrial failure and electrophysiological maturity converge in Parkinson's iPSC-dopamine neurons.
Beccano-Kelly DA, Cherubini M, Mousba Y, Cramb KML, Giussani S et al. (2023), iScience, 26(7), 107044
BibTeX
@article{calciumdysregul-2023/7,
title={Calcium dysregulation combined with mitochondrial failure and electrophysiological maturity converge in Parkinson's iPSC-dopamine neurons.},
author={Beccano-Kelly DA, Cherubini M, Mousba Y, Cramb KML, Giussani S et al.},
journal={iScience},
volume={26},
pages={107044},
year = "2023"
}
Multi-objective point cloud autoencoders for explainable myocardial infarction prediction
Beetz M, Banerjee A & Grau V (2023)
BibTeX
@misc{multiobjectivep-2023/7,
title={Multi-objective point cloud autoencoders for explainable myocardial
infarction prediction},
author={Beetz M, Banerjee A & Grau V},
year = "2023"
}
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Beetz M, Banerjee A & Grau V (2023)
BibTeX
@misc{modelingdcardia-2023/7,
title={Modeling 3D cardiac contraction and relaxation with point cloud
deformation networks},
author={Beetz M, Banerjee A & Grau V},
year = "2023"
}
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Beetz M, Banerjee A, Ossenberg-Engels J & Grau V (2023)
BibTeX
@misc{multiclasspoint-2023/7,
title={Multi-class point cloud completion networks for 3D cardiac anatomy
reconstruction from cine magnetic resonance images},
author={Beetz M, Banerjee A, Ossenberg-Engels J & Grau V},
year = "2023"
}
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks
Beetz M, Yang Y, Banerjee A, Li L & Grau V (2023)
BibTeX
@misc{dshapebasedmyoc-2023/7,
title={3D Shape-Based Myocardial Infarction Prediction Using Point Cloud
Classification Networks},
author={Beetz M, Yang Y, Banerjee A, Li L & Grau V},
year = "2023"
}