Biography
Abhirup Banerjee is a Royal Society University Research Fellow, Full Member of Faculty, and PI in the Department of Engineering Science, University of Oxford. His research is primarily focused on Multimodal Reconstruction of Digital Anatomy for Real-Time Clinical Interventions. Dr Banerjee received the BSc (Hons) and Master degrees in Statistics from the University of Calcutta and the Indian Statistical Institute, respectively. He obtained the PhD degree in Computer Science in March 2017 from the Indian Statistical Institute, Kolkata for his dissertation on Rough-Probabilistic Models for Segmentation and Bias Field Correction in Brain MRI.
He joined the University of Oxford as Postdoctoral Researcher in the Division of Cardiovascular Medicine (CVM), Radcliffe Department of Medicine in August 2017. Dr Banerjee’s research interest spans Biomedical Engineering, Computer Science, and classical Statistics, focusing on a range of topics including Biomedical Image Analysis, Machine Learning, AI, Geometric Deep Learning, Image Processing, Statistical Pattern Recognition, etc. He has served as PI to a Data Study Group project in the Alan Turing Institute. He has received the Young Scientist Award from the Indian Science Congress Association in the year 2016-2017.
Awards and Honours
- The Young Scientist Award from the Indian Science Congress Association in the year 2016-2017 in the Section of Information and Communication Science & Technology (including Computer Sciences).
Most Recent Publications
Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19.
Shanmuganathan M, Kotronias RA, Burrage MK, Ng Y, Banerjee A et al. (2023), Front Cardiovasc Med, 10, 1097974
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 et al. (2022), JACC: Cardiovascular Imaging
Interpretable cardiac anatomy modeling using variational mesh autoencoders.
Beetz M, Corral Acero J, Banerjee A, Eitel I, Zacur E et al. (2022), Frontiers in cardiovascular medicine, 9, 983868
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 et al. (2022), Scientific reports, 12(1), 18220
Automated Torso Contour Extraction from Clinical Cardiac MR Slices for 3D Torso Reconstruction.
Smith HJ, Banerjee A, Choudhury RP & Grau V (2022), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022, 3809-3813
Research Interests
Dr Banerjee’s research interests are primarily focused on (but not limited to) Multimodal Reconstruction and Analysis of Digital Anatomy for Real-Time Clinical Interventions; in particular Segmentation, Landmark Detection, Tracking, Motion Modelling, Reconstruction, Registration, and Fusion of 2D/3D/3D+t Human Anatomical Structures (Cardiovascular, Cerebral, Biliary System, etc.) and Physiological information from Multi-Modality including X-ray, Angiography, MRI, CT, US, etc.
Grants
- Multimodal Reconstruction of Digital Heart for Cardiac Interventions in Real-Time: The Royal Society University Research Fellowship, June 2022 (Principal Investigator).
- Development of A System for Real Time Integration and Display of Quantitative Multi-modality Data During Cardiac Catheterisation: British Heart Foundation, March 2020 (Co-Applicant 1).
Current Projects
- Multimodal Reconstruction of Digital Heart for Cardiac Interventions in Real-Time.
- Building Personalised Heart and Torso Models from Clinical MRI Scans for Simulation of Cardiac Electromechanics.
- Rough-Probabilistic Modelling for Brain MRI Analysis, etc.
Research Groups
Most Recent Publications
Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19.
Shanmuganathan M, Kotronias RA, Burrage MK, Ng Y, Banerjee A et al. (2023), Front Cardiovasc Med, 10, 1097974
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 et al. (2022), JACC: Cardiovascular Imaging
Interpretable cardiac anatomy modeling using variational mesh autoencoders.
Beetz M, Corral Acero J, Banerjee A, Eitel I, Zacur E et al. (2022), Frontiers in cardiovascular medicine, 9, 983868
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 et al. (2022), Scientific reports, 12(1), 18220
Automated Torso Contour Extraction from Clinical Cardiac MR Slices for 3D Torso Reconstruction.
Smith HJ, Banerjee A, Choudhury RP & Grau V (2022), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022, 3809-3813
DPhil & Postdoc Opportunities
If you are Interested in embarking on a journey together on solving Real-life Biomedical problems with Clinical Impacts, please contact me via Email, LinkedIn, or Twitter.
Current Open Positions:
- Postdoctoral Research Assistant (Deadline: Noon on 2 March 2023)
- Research Studentship in Biomedical Image Analysis (Deadline: Noon on 1 March 2023)
Most Recent Publications
Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19.
Shanmuganathan M, Kotronias RA, Burrage MK, Ng Y, Banerjee A et al. (2023), Front Cardiovasc Med, 10, 1097974
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 et al. (2022), JACC: Cardiovascular Imaging
Interpretable cardiac anatomy modeling using variational mesh autoencoders.
Beetz M, Corral Acero J, Banerjee A, Eitel I, Zacur E et al. (2022), Frontiers in cardiovascular medicine, 9, 983868
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 et al. (2022), Scientific reports, 12(1), 18220
Automated Torso Contour Extraction from Clinical Cardiac MR Slices for 3D Torso Reconstruction.
Smith HJ, Banerjee A, Choudhury RP & Grau V (2022), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022, 3809-3813
