Dr
Abhirup Banerjee
BSc MStat PhD
Royal Society University Research Fellow
Full Member of Faculty
Research Fellow at Wolfson College
Email:
College: Wolfson College
Location: Institute of Biomedical Engineering, Old Road Campus Research Building, Oxford OX3 7DQ

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.

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.

Biomedical Image Analysis

Mr Mohammad Atwany - DPhil Student
Dr Alexander Sharp - DPhil Student
Miss Siyu Wang - DPhil Student
Mr Haobo Zhu - DPhil Student

  • 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.

If you are Passionate embarking on a journey together on solving Real-life Biomedical problems with Clinical Impacts, please contact me via Email, LinkedIn, or Twitter. At the moment, I have openings for both DPhil student and Postdoctoral Researcher in my Team.

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).

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)
Predicting 3D cardiac deformations with point cloud autoencoders
Beetz M,  Ossenberg-Engels J,  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)
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)