A
Abhirup Banerjee
Researcher at University of Oxford
Publications - 50
Citations - 418
Abhirup Banerjee is an academic researcher from University of Oxford. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 6, co-authored 24 publications receiving 162 citations. Previous affiliations of Abhirup Banerjee include Indian Statistical Institute.
Papers
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Journal ArticleDOI
Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.
Abhirup Banerjee,Surajit Ray,Bart Vorselaars,Joanne Kitson,Michail Mamalakis,Simonne Weeks,Mark Baker,Louise MacKenzie +7 more
TL;DR: Machine learning, an artificial neural network (ANN) and a simple statistical test are used to identify SARS-CoV-2 positive patients from full blood counts without knowledge of symptoms or history of the individuals to greatly improve initial screening for patients where PCR based diagnostic tools are limited.
Journal ArticleDOI
Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images
Abhirup Banerjee,Pradipta Maji +1 more
TL;DR: A novel approach for simultaneous segmentation and bias field correction in brain MR images is presented, which integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution.
Journal ArticleDOI
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays.
Michail Mamalakis,Andrew J. Swift,Bart Vorselaars,Surajit Ray,Simonne Weeks,Weiping Ding,Richard H. Clayton,Louise MacKenzie,Abhirup Banerjee +8 more
TL;DR: DenResCov-19 as mentioned in this paper is a new deep transfer learning pipeline, which consists of the existing DenseNet-121 and the ResNet-50 networks to diagnose patients with COVID-19, pneumonia, TB or healthy based on CXR images.
Journal ArticleDOI
Rough-probabilistic clustering and hidden Markov random field model for segmentation of HEp-2 cell and brain MR images
Abhirup Banerjee,Pradipta Maji +1 more
TL;DR: A new clustering algorithm, termed as rough-probabilistic clustering, is presented, integrating judiciously the merits of rough sets and a new probability distribution, called stomped normal (SN) distribution, for accurate and robust segmentation of images.
Proceedings ArticleDOI
Biventricular Surface Reconstruction From Cine Mri Contours Using Point Completion Networks
TL;DR: In this article, a deep learning method acting directly on point clouds is proposed to reconstruct a dense 3D biventricular heart model from misaligned 2D cardiac MR image contours.