Anil Anthony Bharath

About Anil Anthony Bharath

Anil Anthony Bharath, With an exceptional h-index of 30 and a recent h-index of 23 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of Convolutional Neural Networks, Deep Learning, Biologically-Inspired Algorithms, Imaging, Healthcare.

His recent articles reflect a diverse array of research interests and contributions to the field:

Quality assurance of late gadolinium enhancement cardiac MRI images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to …

Advancing Left Atrial MRI Evaluation: 3D Motion Atlas Characterization Using an Unsupervised Image Registration Network

Automatic Quality Assurance of Late Gadolinium enhancement CMR Images: A Deep Learning Classifier for abnormality-likelihood with Potential to Prompt Real-time Image Optimisation

18 Automated vendor-independent detection and quantification of aortic stenosis from a 3-chamber bSSFP cine view

Estimation of fibre architecture and scar in myocardial tissue using electrograms: An in-silico study

Aortic stenosis assessment from the 3-chamber cine: ratio of balanced steady-state-free-precession (bSSFP) blood signal between the aorta and left ventricle predicts severity

Signal processing in computational video and video streaming

High-Resolution Maps of Left Atrial Displacements and Strains Estimated with 3D CINE MRI and Unsupervised Neural Networks

Anil Anthony Bharath Information

University

Position

Dept of Bioengineering

Citations(all)

11066

Citations(since 2020)

8240

Cited By

4957

hIndex(all)

30

hIndex(since 2020)

23

i10Index(all)

79

i10Index(since 2020)

47

Email

University Profile Page

Google Scholar

Anil Anthony Bharath Skills & Research Interests

Convolutional Neural Networks

Deep Learning

Biologically-Inspired Algorithms

Imaging

Healthcare

Top articles of Anil Anthony Bharath

Quality assurance of late gadolinium enhancement cardiac MRI images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to …

Journal of Cardiovascular Magnetic Resonance

2024/3/24

Advancing Left Atrial MRI Evaluation: 3D Motion Atlas Characterization Using an Unsupervised Image Registration Network

Journal of Cardiovascular Magnetic Resonance

2024/3/1

Automatic Quality Assurance of Late Gadolinium enhancement CMR Images: A Deep Learning Classifier for abnormality-likelihood with Potential to Prompt Real-time Image Optimisation

Journal of Cardiovascular Magnetic Resonance

2024/3/1

18 Automated vendor-independent detection and quantification of aortic stenosis from a 3-chamber bSSFP cine view

2024/3/1

Estimation of fibre architecture and scar in myocardial tissue using electrograms: An in-silico study

Biomedical Signal Processing and Control

2024/3/1

Aortic stenosis assessment from the 3-chamber cine: ratio of balanced steady-state-free-precession (bSSFP) blood signal between the aorta and left ventricle predicts severity

Journal of Cardiovascular Magnetic Resonance

2024/1/9

Signal processing in computational video and video streaming

2024/1/5

High-Resolution Maps of Left Atrial Displacements and Strains Estimated with 3D CINE MRI and Unsupervised Neural Networks

arXiv preprint arXiv:2312.09387

2023/12/14

High-resolution 3D Maps of Left Atrial Displacements using an Unsupervised Image Registration Neural Network

arXiv preprint arXiv:2309.02179

2023/9/5

Current and emerging deep-learning methods for the simulation of fluid dynamics

2023/7/26

Disentangled generative models for robust prediction of system dynamics

ICML 2023, International Conference on Machine Learning

2023/6/15

Prototype of a Cardiac MRI Simulator for the Training of Supervised Neural Networks

2023/6/16

Automatic Aortic Valve Pathology Detection from 3-Chamber Cine MRI with Spatio-Temporal Attention Maps

2023/6/16

Ratio of aortic to left ventricle SSFP blood signal in a single 3-chamber view correlates with aortic stenosis severity

European Heart Journal-Cardiovascular Imaging

2023/6

automatic detection of aortic valve pathology using 3-chamber cine MRI

European Heart Journal-Cardiovascular Imaging

2023/6

182 Late gadolinium enhancement following covid-19 infection does not predict outcome: a single-centre study

2023/6/1

175 Novel cmr radiomic correlates with aortic stenosis severity in a single 3-chamber view

2023/6/1

Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level …

Journal of medical artificial intelligence

2023/4/1

Validity of self-testing at home with rapid severe acute respiratory syndrome coronavirus 2 antibody detection by lateral flow immunoassay

Clinical Infectious Diseases

2023/2/15

TMS-Net: A segmentation network coupled with a run-time quality control method for robust cardiac image segmentation

Computers in Biology and Medicine

2023/1/1

See List of Professors in Anil Anthony Bharath University(Imperial College London)

Co-Authors

academic-engine