Publications by person

Abhirup Banerjee

MStat PhD FDIRDI

Royal Society University Research Fellow

Research Fellow at Wolfson College

Principal Investigator

Research

Impact

All publications by Dr Banerjee

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, Banerjee A, et al. (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, Rodriguez B, Banerjee A, Grau V, et al. (2025)

Self-supervised Instance Segmentation of Diabetic Foot Ulcers via Feature Correspondence Distillation
Zhang W, Banerjee A, Ray S, et al. (2025)

Editorial: Artificial intelligence applications for cancer diagnosis in radiology
Banerjee A, Shan H, Feng R, et al. (2025)

Deep learning based coronary vessels segmentation in X-ray angiography using temporal information
He H, Banerjee A, Choudhury RP, Grau V, et al. (2025)

Automated Coronary Vessels Segmentation in X-ray Angiography Using Graph Attention Network
He H, Banerjee A, Choudhury RP, Grau V, et al. (2024)

Generating Virtual Populations of 3D Cardiac Anatomies with Snowflake-Net
Peng J, Beetz M, Banerjee A, Chen M, Grau V, et al. (2024)

Scoring systems developed by machine learning: intelligent but simple to use?
Banerjee A, Leeson P, et al. (2024)

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, Rodriguez B, Grau V, et al. (2024)

INtra-procedural ultraSound Imaging for DEtermination of atrial wall thickness and acute tissue changes after isolation of the Pulmonary Veins with radiofrequency, cryoballoon or laser balloon energy: the INSIDE PVs Study
Leo M, Maria GLD, Gala ABE, Pope M, Banerjee A, Kelion A, Pedersen M, Rajappan K, Ginks M, Bashir Y, Hunter R, Betts T, et al. (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 R, Burrage M, Arvidsson P, Banerjee A, Çakir I, Seemann F, Heiberg E, Peters D, Zhang Q, Channon K, Piechnik S, Ferreira V, et al. (2024)

Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.
Beetz M, Banerjee A, Grau V, et al. (2024)

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, Langrish J, Lucking A, Pitcher A, Gara E, Banerjee A, Kharbanda R, Choudhury R, Banning A, De Maria GL, Piechnik S, Channon K, Ferreira V, et al. (2024)

Automated continuous rhythm monitoring with implantable cardiac monitor and real-time smartphone alerts during af episodes: SMART-ALERT study
Gala ABE, Pope MTB, Leo M, Sharp AJ, Varini R, Paisey JR, Curzen N, Banerjee A, Betts TR, et al. (2024)

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, Betts TR, 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, Betts TR, et al. (2024)

Clinical Utility of Cardiovascular Magnetic Resonance Before Invasive Coronary Angiography in Suspected Non-ST-segment-Elevation Myocardial Infarction
Shanmuganathan M, Nikolaidou C, Burrage MK, Borlotti A, Kotronias R, Scarsini R, Banerjee A, Terentes-Printzios D, Pitcher A, Gara E, Langrish J, Lucking A, Choudhury R, De Maria GL, Banning A, investigators OS, Piechnik SK, Channon KM, Ferreira VM, et al. (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, Whitehouse D, Menon D, Newcombe V, Voets N, Banerjee A, Kamnitsas K, et al. (2024)

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.
Nan Y, Xing X, ShiyiWang , Tang Z, Felder FN, Zhang S, Ledda RE, Ding X, Yu R, Liu W, Shi F, Sun T, Cao Z, Zhang M, Gu Y, Zhang H, Gao J, Wang P, Tang W, Yu P, Kang H, Chen J, Lu X, Zhang B, Mamalakis M, Prinzi F, Carlini G, Cuneo L, Banerjee A, Xing Z, Zhu L, Mesbah Z, Jain D, Mayet T, Yuan H, Lyu Q, Qayyum A, Mazher M, Wells A, Walsh SL, Yang G, et al. (2024)

Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories
Lashgari M, Choudhury RP, Banerjee A, et al. (2024)

Deep Learning-based 3D Coronary Tree Reconstruction from Two 2D Non-simultaneous X-ray Angiography Projections
Wang Y, Banerjee A, Choudhury RP, Grau V, et al. (2024)

Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review
Sharp AJ, Betts TR, Banerjee A, et al. (2024)

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, Rajappan K, Ginks M, Bashir Y, Hunter RJ, Betts T, et al. (2024)

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, Swift AJ, Panoutsos G, Vorselaars B, et al. (2024)

Modelling Multi-Phase Cardiac Anatomy Using Point Cloud Variational Autoencoders
Seale T, Beetz M, Rodriguez B, Grau V, Banerjee A, et al. (2024)

NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections by Neural Implicit Representation
Wang Y, Banerjee A, Grau V, et al. (2024)

Uncertainty Quantification in Deep Learning Framework for Mallampati Classification
Mahato A, Sarangi P, Kurmi VK, Banerjee A, Goyal A, Basu T, et al. (2024)

TCPNet: A Novel Tumor Contour Prediction Network Using MRIs
Agarwal S, Kurmi VK, Banerjee A, Basu T, et al. (2024)

New Trends of Adversarial Machine Learning for Data Fusion and Intelligent System
Ding W, Zhang Z, Martínez L, Huang Y, Cao Z, Liu J, Banerjee A, et al. (2024)

Modeling the mechanisms of non-neurogenic dynamic cerebral autoregulation
van Zijl N, Banerjee A, Payne SJ, et al. (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, et al. (2024)

Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation
Sharp AJ, Pope MTB, Gala ABE, Varini R, Betts TR, Banerjee A, et al. (2024)

NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections via Neural Implicit Representation
Wang Y, Banerjee A, Grau V, et al. (2024)

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, Leeson P, et al. (2024)

Characterization of A Robust Probabilistic Framework for Brain MR Image Data Distributions
Banerjee A, Mukhoti SK, et al. (2023)

Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19
Shanmuganathan M, Kotronias RA, Burrage MK, Ng Y, Banerjee A, Xie C, Fletcher A, Manley P, Borlotti A, Emfietzoglou M, Mentzer AJ, Marin F, Raman B, Tunnicliffe EM, et al. (2023)

3D shape-based myocardial infarction prediction using point cloud classification networks
Beetz M, Yang Y, Banerjee A, Li L, Grau V, et al. (2023)

Influence of myocardial infarction on QRS properties: a simulation study
Li L, Camps J, Wang Z, Banerjee A, Rodriguez B, Grau V, et al. (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, Caiazza MC, Rai P, Vingill S, Bengoa-Vergniory N, Ng B, Corda G, Banerjee A, Vowles J, Cowley S, Wade-Martins R, et al. (2023)

3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks
Beetz M, Yang Y, Banerjee A, Li L, Grau V, et al. (2023)

Multi-objective point cloud autoencoders for explainable myocardial infarction prediction
Beetz M, Banerjee A, Grau V, et al. (2023)

Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Beetz M, Banerjee A, Grau V, et al. (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, et al. (2023)

PO-03-104 MRI VERSUS ULTRASOUND: EXPLORING THE INFLUENCE OF IMAGING MODALITY ON THE FIDELITY OF NON-CONTACT CHARGE DENSITY MAPPING
Sharp AJ, Good W, Melki L, Pope MT, Wijesurendra R, Briosa e Gala A, Betts TR, Banerjee A, et al. (2023)

Multi-objective Point Cloud Autoencoders for Explainable Myocardial Infarction Prediction
Beetz M, Banerjee A, Grau V, et al. (2023)

Left atrium surface mesh reconstruction from cardiac MRI
Sharp A, Pope MTB, Wijesurendra R, Gala A, Betts TR, Banerjee A, et al. (2023)

Anatomical basis of sex differences in human post-myocardial infarction ECG phenotypes identified by novel automated torso-cardiac 3D reconstruction
Smith HJ, Rodriguez B, Sang Y, Beetz M, Choudhury R, Grau V, Banerjee A, et al. (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, Hadjileontiadis L, Khandoker A, Lewandowski AJ, Banerjee A, Leeson P, et al. (2023)

Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference
Li L, Camps J, Zhinuo , Wang , Banerjee A, Beetz M, Rodriguez B, Grau V, et al. (2023)

Influence of Myocardial Infarction on QRS Properties: A Simulation Study
Li L, Camps J, Zhinuo , Wang , Banerjee A, Rodriguez B, Grau V, et al. (2023)

Predicting 3D cardiac deformations with point cloud autoencoders
Beetz M, Ossenberg-Engels J, Banerjee A, Grau V, et al. (2022)

Generating subpopulation-specific biventricular anatomy models using conditional point cloud variational autoencoders
Beetz M, Banerjee A, Grau V, et al. (2022)

Rapid neutrophil mobilization by VCAM-1+ endothelial cell-derived extracellular vesicles
Akbar N, Braithwaite AT, Corr EM, Koelwyn GJ, van Solingen C, Cochain C, Saliba A-E, Corbin A, Pezzolla D, Møller Jørgensen M, Bæk R, Edgar L, De Villiers C, Gunadasa-Rohling M, Banerjee A, Paget D, Lee C, Hogg E, Costin A, Dhaliwal R, Johnson E, Krausgruber T, Riepsaame J, Melling GE, et al. (2022)

Semi-supervised coronary vessels segmentation from invasive coronary angiography with connectivity-preserving loss function
He H, Banerjee A, Beetz M, Choudhury RP, Grau V, Ieee , et al. (2022)

Combined generation of electrocardiogram and cardiac anatomy models using multi-modal variational autoencoders
Beetz M, Banerjee A, Sang Y, Grau V, et al. (2022)

Lesion Size Index (LSI)–guided catheter ablation for atrial fibrillation: can tissue impedance drop help to identify desirable ablation settings and target indices?
Leo M, Banerjee A, Gala AB, Pope M, Pedersen M, Rajappan K, Ginks M, Bashir Y, Hunter RJ, Betts T, et al. (2022)

Multi-domain variational autoencoders for combined modeling of MRI-based biventricular anatomy and ECG-based cardiac electrophysiology
Beetz M, Banerjee A, Grau V, et al. (2022)

Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers
Boss AN, Banerjee A, Mamalakis M, Ray S, Swift AJ, Wilkie C, Fanstone JW, Vorselaars B, Cole J, Weeks S, Mackenzie LS, et al. (2022)

Automated torso contour extraction from clinical cardiac MR slices for 3D torso reconstruction
Smith HJ, Banerjee A, Choudhury RP, Grau V, et al. (2022)

Automated 3D whole-heart mesh reconstruction from 2D cine MR slices using statistical shape model
Banerjee A, Zacur E, Choudhury RP, Grau V, et al. (2022)

Reconstructing 3D cardiac anatomies from misaligned multi-view magnetic resonance images with Mesh Deformation U-Nets
Beetz M, Banerjee A, Grau V, et al. (2022)

A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest X-rays
Ray S, Banerjee A, Swift A, Fanstone JW, Mamalakis M, Vorselaars B, Wilkie C, Cole J, Mackenzie LS, Weeks S, et al. (2022)

Acute response in the noninfarcted myocardium predicts long-term major adverse cardiac events after STEMI
Shanmuganathan M, Masi A, Burrage MK, Kotronias RA, Borlotti A, Scarsini R, Banerjee A, Terentes-Printzios D, Zhang Q, Hann E, Tunnicliffe E, Lucking A, Langrish J, Kharbanda R, De Maria GL, Banning AP, Choudhury RP, Channon KM, Piechnik SK, Ferreira VM, et al. (2022)

Interpretable cardiac anatomy modeling using variational mesh autoencoders
Beetz M, Corral Acero J, Banerjee A, Eitel I, Zacur E, Lange T, Stiermaier T, Evertz R, Backhaus SJ, Thiele H, Bueno-Orovio A, Lamata P, Schuster A, Grau V, et al. (2022)

Post-Infarction Risk Prediction with Mesh Classification Networks
Beetz M, Acero JC, Banerjee A, Eitel I, Zacur E, Lange T, Stiermaier T, Evertz R, Backhaus SJ, Thiele H, Bueno-Orovio A, Lamata P, Schuster A, Grau V, et al. (2022)

Mesh U-Nets for 3D Cardiac Deformation Modeling
Beetz M, Acero JC, Banerjee A, Eitel I, Zacur E, Lange T, Stiermaier T, Evertz R, Backhaus SJ, Thiele H, Bueno-Orovio A, Lamata P, Schuster A, Grau V, et al. (2022)

Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction
Beetz M, Banerjee A, Grau V, et al. (2022)

Deep Computational Model for the Inference of Ventricular Activation Properties
Li L, Camps J, Banerjee A, Beetz M, Rodriguez B, Grau V, et al. (2022)

Reconstructing 3D Cardiac Anatomies from Misaligned Multi-View Magnetic Resonance Images with Mesh Deformation U-Nets
Beetz M, Banerjee A, Grau V, et al. (2022)

Deep Computational Model for the Inference of Ventricular Activation Properties
Li L, Camps J, Banerjee A, Beetz M, Rodriguez B, Grau V, et al. (2022)

Biventricular surface reconstruction from cine MRI contours using point completion networks
Beetz M, Banerjee A, Grau Colomer V, et al. (2021)

DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays
Mamalakis M, Swift AJ, Vorselaars B, Ray S, Weeks S, Ding W, Clayton RH, Mackenzie LS, Banerjee A, et al. (2021)

LUCAS: A highly accurate yet simple risk calculator that predicts survival of COVID-19 patients using rapid routine tests
Ray S, Swift A, Fanstone JW, Banerjee A, Mamalakis M, Vorselaars B, Mackenzie LS, Weeks S, et al. (2021)

Optimised misalignment correction from cine MR slices using statistical shape model
Banerjee A, Zacur E, Grau V, Choudhury RP, et al. (2021)

INtra-procedural ultraSound Imaging for DEtermination of atrial wall thickness and acute tissue changes after isolation of the pulmonary veins with radiofrequency, cryoballoon or laser balloon energy: the INSIDE PVs study
Leo M, De Maria GL, Briosa E Gala A, Pope M, Banerjee A, Kelion A, Pedersen M, Rajappan K, Ginks M, Bashir Y, Hunter RJ, Betts T, et al. (2021)

A completely automated pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices
Banerjee A, Camps J, Zacur E, Andrews CM, Rudy Y, Choudhury RP, Rodriguez B, Grau V, et al. (2021)

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays.
Mamalakis M, Swift AJ, Vorselaars B, Ray S, Weeks S, Ding W, Clayton RH, Mackenzie LS, Banerjee A, et al. (2021)

1 Long-term prognosis after acute ST-segment elevation myocardial infarction is determined by characteristics in both non-infarcted and infarcted myocardium on cardiovascular magnetic resonance imaging
Shanmuganathan M, Masi A, Burrage MK, Kotronias RA, Borlotti A, Scarsini R, Banerjee A, Terentes-Printzios D, Zhang Q, Hann E, Tunnicliffe E, Lucking A, Langrish J, Kharbanda R, Luigi de Maria G, Banning AP, Choudhury RP, Channon KM, Piechnik SK, Ferreira VM, et al. (2021)

Long-term prognosis after acute ST-segment elevation myocardial infarction is determined by characteristics in both non-infarcted and infarcted myocardium on cardiovascular magnetic resonance imaging
Shanmuganathan M, Masi A, Burrage MK, Kotronias RA, Borlotti A, Scarsini R, Banerjee A, Terentes-Printzios D, Zhang Q, Hann E, Tunnicliffe E, Lucking A, Langrish J, Kharbanda R, de Maria GL, Banning AP, Choudhury RP, Channon KM, Piechnik SK, Ferreira VM, et al. (2021)

LUCAS: development and validation of a simple mortality risk calculator that predicts 60-day survival of adult SARS-CoV-2 positive patients at hospital admission using rapid routine tests
Ray S, Swift A, Fanstone JW, Banerjee A, Mamalakis M, Vorselaars B, Mackenzie LS, Weeks S, et al. (2021)

Insights into electrophysiological mechanisms of atrial fibrillation propagation using simultaneous bi-atrial mapping
Pope M, Kuklik P, Banerjee A, Briosa e Gala A, Leo M, Mahmoudi M, Paisey J, Betts T, et al. (2021)

INtra-Procedural UltraSound Imaging for DEtermination of Atrial Wall Thickness and Acute Tissue Changes After Isolation of the Pulmonary Veins with Radiofrequency, Cryoballoon or Laser Balloon Energy: the INSIDE PVs Study
Leo M, De Maria GL, Gala AB, Pope M, Banerjee A, Kelion A, Pedersen M, Rajappan K, Ginks M, Bashir Y, Hunter R, Betts T, et al. (2021)

Characterization of a Robust Probabilistic Framework for Image Data Distributions
Banerjee A, Mukhoti S, et al. (2021)

Poor and Sick Newsboy Model: A Robust Generalisation with Misspecified Demand
Mukhoti S, Banerjee A, et al. (2021)

A spatially constrained probabilistic model for robust image segmentation
Banerjee A, Maji P, et al. (2020)

Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population
Banerjee A, Ray S, Vorselaars B, Kitson J, Mamalakis M, Weeks S, Baker M, Mackenzie LS, et al. (2020)

Endothelial cell-derived extracellular vesicles elicit neutrophil deployment from the spleen following acute myocardial infarction
Akbar N, Braithwaite A, Corr E, Koelwyn G, van Solingen C, Cochain C, Saliba A-E, Corbin A, Pezzolla D, Edgar L, Gunadasa-Rohling M, Banerjee A, Paget D, Lee C, Hogg E, Costin A, Dhaliwal R, Johnson E, Krausgruber T, Riepsaame J, Melling G, Shanmuganathan M, Acute Myocardial Infarction Study O, Bock C, Carter D, et al. (2020)

Automated Motion Correction and 3D Vessel Centerlines Reconstruction from Non-simultaneous Angiographic Projections
Banerjee A, Kharbanda R, Choudhury R, Grau V, et al. (2019)

Endothelial cell derived extracellular vesicles mediate neutrophil deployment from the spleen following acute myocardial infarction
Akbar N, Corbin A, Dawkins S, Lee C, Hogg E, Edgar L, Gunadasa-Rohling M, Banerjee A, Melling G, Dragovic R, Carter D, Riley P, Udalova I, Channon KM, Anthony D, Choudhury RP, Infarction OAM, et al. (2019)

Segmentation of bias field induced brain MR images using rough sets and stomped-t distribution
Banerjee A, Maji P, et al. (2019)

Point-cloud method for automated 3D coronary tree reconstruction from multiple non-simultaneous angiographic projections
Banerjee A, Galassi F, Zacur E, De Maria GL, Choudhury R, Grau V, et al. (2019)

Optimized Rigid Motion Correction from Multiple Non-simultaneous X-Ray Angiographic Projections
Banerjee A, Choudhury RP, Grau V, et al. (2019)

Impaired myocardial healing in patients with diabetes after ST-elevation myocardial infarction
Oxford Acute Myocardial Infarction (OxAMI) Study , Wamil M, Borlotti A, Banerjee A, Gaughran L, De Maria G, Banning A, Kharbanda R, Choudhury R, et al. (2019)

Endothelial cell derived extracellular vesicles mediate immune cell deployment from the spleen and transcriptional programming following acute myocardial infarction
Akbar N, Corbin A, Hogg E, Banerjee A, Lee C, Melling G, Edgar L, Dragovic R, Carter D, Riley P, Udalova I, Anthony D, Choudhury R, et al. (2019)

Spatially constrained student’s t-distribution based mixture model for robust image segmentation
Banerjee A, Maji P, et al. (2018)

Stomped-t: A novel probability distribution for rough-probabilistic clustering
Banerjee A, Maji P, et al. (2017)

Rough-probabilistic clustering and hidden Markov random field model for segmentation of HEp-2 cell and brain MR images
Banerjee A, Maji P, et al. (2016)

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.
Banerjee A, Maji P, et al. (2015)

Rough Sets for Finite Mixture Model Based HEp-2 Cell Segmentation
Banerjee A, Maji P, et al. (2015)

Rough sets for bias field correction in MR images using contraharmonic mean and quantitative index.
Banerjee A, Maji P, et al. (2013)

Rough Set Based Homogeneous Unsharp Masking for Bias Field Correction in MRI
Banerjee A, Maji P, et al. (2013)

Contraharmonic Mean Based Bias Field Correction in MR Images
Banerjee A, Maji P, et al. (2013)

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.
Banerjee A, Maji P, et al. ()

Rough sets for bias field correction in MR images using contraharmonic mean and quantitative index.
Banerjee A, Maji P, et al. ()

Spatially constrained student’s t-distribution based mixture model for robust image segmentation
Banerjee A, Maji P, et al. ()

Stomped-t: A novel probability distribution for rough-probabilistic clustering
Banerjee A, Maji P, et al. ()

Rough-probabilistic clustering and hidden Markov random field model for segmentation of HEp-2 cell and brain MR images
Banerjee A, Maji P, et al. ()

Rough Sets for Finite Mixture Model Based HEp-2 Cell Segmentation
Banerjee A, Maji P, et al. ()

Rough Set Based Homogeneous Unsharp Masking for Bias Field Correction in MRI
Banerjee A, Maji P, et al. ()

Contraharmonic Mean Based Bias Field Correction in MR Images
Banerjee A, Maji P, et al. ()

Automated Motion Correction and 3D Vessel Centerlines Reconstruction from Non-simultaneous Angiographic Projections
Banerjee A, Kharbanda R, Choudhury R, Grau V, et al. ()

Segmentation of bias field induced brain MR images using rough sets and stomped-t distribution
Banerjee A, Maji P, et al. ()

Point-cloud method for automated 3D coronary tree reconstruction from multiple non-simultaneous angiographic projections
Banerjee A, Galassi F, Zacur E, De Maria GL, Choudhury R, Grau V, et al. ()

Optimized Rigid Motion Correction from Multiple Non-simultaneous X-Ray Angiographic Projections
Banerjee A, Choudhury RP, Grau V, et al. ()

A spatially constrained probabilistic model for robust image segmentation
Banerjee A, Maji P, et al. ()

Biventricular surface reconstruction from cine MRI contours using point completion networks
Beetz M, Banerjee A, Grau Colomer V, et al. ()

Optimised misalignment correction from cine MR slices using statistical shape model
Banerjee A, Zacur E, Grau V, Choudhury RP, et al. ()

Predicting 3D cardiac deformations with point cloud autoencoders
Beetz M, Ossenberg-Engels J, Banerjee A, Grau V, et al. ()

Generating subpopulation-specific biventricular anatomy models using conditional point cloud variational autoencoders
Beetz M, Banerjee A, Grau V, et al. ()

Semi-supervised coronary vessels segmentation from invasive coronary angiography with connectivity-preserving loss function
He H, Banerjee A, Beetz M, Choudhury RP, Grau V, Ieee , et al. ()

Combined generation of electrocardiogram and cardiac anatomy models using multi-modal variational autoencoders
Beetz M, Banerjee A, Sang Y, Grau V, et al. ()

Multi-domain variational autoencoders for combined modeling of MRI-based biventricular anatomy and ECG-based cardiac electrophysiology
Beetz M, Banerjee A, Grau V, et al. ()

Automated torso contour extraction from clinical cardiac MR slices for 3D torso reconstruction
Smith HJ, Banerjee A, Choudhury RP, Grau V, et al. ()

Automated 3D whole-heart mesh reconstruction from 2D cine MR slices using statistical shape model
Banerjee A, Zacur E, Choudhury RP, Grau V, et al. ()

Reconstructing 3D cardiac anatomies from misaligned multi-view magnetic resonance images with Mesh Deformation U-Nets
Beetz M, Banerjee A, Grau V, et al. ()

Characterization of A Robust Probabilistic Framework for Brain MR Image Data Distributions
Banerjee A, Mukhoti SK, et al. ()

Point2Mesh-Net: Combining Point Cloud and Mesh-Based Deep Learning for Cardiac Shape Reconstruction
Beetz M, Banerjee A, Grau V, et al. ()

Deep Computational Model for the Inference of Ventricular Activation Properties
Li L, Camps J, Banerjee A, Beetz M, Rodriguez B, Grau V, et al. ()

3D shape-based myocardial infarction prediction using point cloud classification networks
Beetz M, Yang Y, Banerjee A, Li L, Grau V, et al. ()

Influence of myocardial infarction on QRS properties: a simulation study
Li L, Camps J, Wang Z, Banerjee A, Rodriguez B, Grau V, et al. ()

3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks
Beetz M, Yang Y, Banerjee A, Li L, Grau V, et al. ()

Multi-objective point cloud autoencoders for explainable myocardial infarction prediction
Beetz M, Banerjee A, Grau V, et al. ()

Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Beetz M, Banerjee A, Grau V, et al. ()

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, et al. ()

Reconstructing 3D Cardiac Anatomies from Misaligned Multi-View Magnetic Resonance Images with Mesh Deformation U-Nets
Beetz M, Banerjee A, Grau V, et al. ()

Multi-objective Point Cloud Autoencoders for Explainable Myocardial Infarction Prediction
Beetz M, Banerjee A, Grau V, et al. ()

Left atrium surface mesh reconstruction from cardiac MRI
Sharp A, Pope MTB, Wijesurendra R, Gala A, Betts TR, Banerjee A, et al. ()

Automated Coronary Vessels Segmentation in X-ray Angiography Using Graph Attention Network
He H, Banerjee A, Choudhury RP, Grau V, et al. ()

Generating Virtual Populations of 3D Cardiac Anatomies with Snowflake-Net
Peng J, Beetz M, Banerjee A, Chen M, Grau V, et al. ()

Scoring systems developed by machine learning: intelligent but simple to use?
Banerjee A, Leeson P, et al. ()

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, Rodriguez B, Grau V, et al. ()

Characterization of a Robust Probabilistic Framework for Image Data Distributions
Banerjee A, Mukhoti S, et al. ()

Poor and Sick Newsboy Model: A Robust Generalisation with Misspecified Demand
Mukhoti S, Banerjee A, et al. ()

Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.
Beetz M, Banerjee A, Grau V, et al. ()

Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories
Lashgari M, Choudhury RP, Banerjee A, et al. ()

Deep Learning-based 3D Coronary Tree Reconstruction from Two 2D Non-simultaneous X-ray Angiography Projections
Wang Y, Banerjee A, Choudhury RP, Grau V, et al. ()

Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review
Sharp AJ, Betts TR, Banerjee A, et al. ()

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, Swift AJ, Panoutsos G, Vorselaars B, et al. ()

Modelling Multi-Phase Cardiac Anatomy Using Point Cloud Variational Autoencoders
Seale T, Beetz M, Rodriguez B, Grau V, Banerjee A, et al. ()

“Real-world” performance of the Confirm Rx™ SharpSense AF detection algorithm: UK Confirm Rx study
Gala ABE, Pope MTB, Leo M, Sharp AJ, Banerjee A, Field D, Thomas H, Balasubramaniam R, Hunter R, Gardner RS, Wilson D, Gallagher MM, Ormerod J, Paisey J, Curzen N, Betts TR, et al. ()

NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections by Neural Implicit Representation
Wang Y, Banerjee A, Grau V, et al. ()

Uncertainty Quantification in Deep Learning Framework for Mallampati Classification
Mahato A, Sarangi P, Kurmi VK, Banerjee A, Goyal A, Basu T, et al. ()

TCPNet: A Novel Tumor Contour Prediction Network Using MRIs
Agarwal S, Kurmi VK, Banerjee A, Basu T, et al. ()

New Trends of Adversarial Machine Learning for Data Fusion and Intelligent System
Ding W, Zhang Z, Martínez L, Huang Y, Cao Z, Liu J, Banerjee A, et al. ()

Modeling the mechanisms of non-neurogenic dynamic cerebral autoregulation
van Zijl N, Banerjee A, Payne SJ, et al. ()

Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation
Sharp AJ, Pope MTB, Gala ABE, Varini R, Betts TR, Banerjee A, et al. ()

NeCA: 3D Coronary Artery Tree Reconstruction from Two 2D Projections via Neural Implicit Representation
Wang Y, Banerjee A, Grau V, et al. ()

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, Banerjee A, et al. ()

Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
Chen C, Li L, Beetz M, Banerjee A, Gupta R, Grau V, et al. ()

Self-supervised Instance Segmentation of Diabetic Foot Ulcers via Feature Correspondence Distillation
Zhang W, Banerjee A, Ray S, et al. ()

Editorial: Artificial intelligence applications for cancer diagnosis in radiology
Banerjee A, Shan H, Feng R, et al. ()

Deep learning based coronary vessels segmentation in X-ray angiography using temporal information
He H, Banerjee A, Choudhury RP, Grau V, et al. ()

Influence of Myocardial Infarction on QRS Properties: A Simulation Study
Li L, Camps J, Zhinuo , Wang , Banerjee A, Rodriguez B, Grau V, et al. ()

Deep Computational Model for the Inference of Ventricular Activation Properties
Li L, Camps J, Banerjee A, Beetz M, Rodriguez B, Grau V, et al. ()

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, Betts TR, et al. ()

Splitting and Merging for Active Contours: Plug-and-Play
Lashgari M, Banerjee A, Rabbani H, et al. ()

Diagnostic Performance of Single-Lead Electrocardiograms from the Apple Watch and CART Ring for Cardiac Arrhythmias
Briosa e Gala A, Sharp AJ, Schraam D, Pope MTB, Leo M, Varini R, Banerjee A, Win KZ, Kalla M, Paisey J, Curzen N, Betts TR, et al. ()

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, et al. ()

Real-time Smartphone Alerts During Atrial Fibrillation Episodes with Implantable Cardiac Monitors and Wearable Devices: SMART-ALERT study.
Briosa E Gala A, Sharp AJ, Pope MTB, Leo M, Varini R, Paisey J, Curzen N, Banerjee A, Betts TR, et al. ()

Single-Source Domain Generalization for Coronary Vessels Segmentation in X-Ray Angiography
Atwany M, Lashgari M, Choudhury RP, Grau V, Banerjee A, et al. ()

Deep conditional generative model for personalization of 12-lead electrocardiograms and cardiovascular risk prediction
Sang Y, Banerjee A, Beetz M, Grau V, et al. ()

Evaluating Convolution, Attention, and Mamba Based U-Net Models for Multi-class Bi-Atrial Segmentation from LGE-MRI
Thesing C, Bueno-Orovio A, Banerjee A, et al. ()

SMART-ALERT study: continuous cardiac monitoring and real-time automated smartphone alerts for atrial fibrillation episodes
Gala ABE, Pope MTP, Leo M, Sharp A, Varini R, Paisey J, Curzen N, Banerjee A, Tim TR, et al. ()