R. Welikala

发表

RESPONSIVITY FOR THE DETECTION OF PROLIFERATIVE DIABETIC RETINOPATHY

A. Hoppe, S. Barman, J. Dehmeshki, 2012 .

S. A. Barman, D. Strachan, A. Rudnicka, 2023, PLoS genetics.

Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke

D. Strachan, A. Rudnicka, S. Barman, 2022, British Journal of Ophthalmology.

Title: Artificial intelligence enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke

R. A. Welikala, S. A. Barman, D. Strachan, 2022 .

Retinal Vascular Tortuosity and Diameter Associations with Adiposity and Components of Body Composition

R. A. Welikala, D. Strachan, A. Rudnicka, 2020, Obesity.

Associations of Retinal Microvascular Diameters and Tortuosity With Blood Pressure and Arterial Stiffness

R. A. Welikala, D. Strachan, A. Rudnicka, 2019, Hypertension.

Automated arteriole and venule classification using deep learning for retinal images from the UK Biobank cohort

Alicja R. Rudnicka, Christopher G. Owen, Sarah Barman, 2017, Comput. Biol. Medicine.

Image quality assessment

Christopher G. Owen, Sarah Barman, R. A. Welikala, 2019, Computational Retinal Image Analysis.

Automated quantification of retinal vessel morphometry in the UK biobank cohort

Muhammad Moazam Fraz, Christopher G. Owen, Peter Whincup, 2017, 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA).

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

Muhammad Moazam Fraz, Alicja R. Rudnicka, Christopher G. Owen, 2016, Comput. Biol. Medicine.

Automated Detection and Classification of Oral Lesions Using Deep Learning for Early Detection of Oral Cancer

Chee Seng Chan, Jian Han Lim, Paolo Remagnino, 2020, IEEE Access.

Retinal Vasculometry Associations With Glaucoma: Findings From the European Prospective Investigation of Cancer–Norfolk Eye Study

R. A. Welikala, D. Strachan, A. Rudnicka, 2020, American journal of ophthalmology.

The establishment of a multi-source dataset of images on common oral lesions

Paolo Remagnino, Sarah Barman, Chee Seng Chan, 2021 .

Automated detection of proliferative diabetic retinopathy using a modified line operator and dual classification

Jamshid Dehmeshki, Sarah Barman, Andreas Hoppe, 2014, Comput. Methods Programs Biomed..

Retinal Vasculometry Associations with Cardiometabolic Risk Factors in the European Prospective Investigation of Cancer—Norfolk Study

R. A. Welikala, D. Strachan, M. Fraz, 2019, Ophthalmology.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy

Jamshid Dehmeshki, Muhammad Moazam Fraz, Sarah Barman, 2015, Comput. Medical Imaging Graph..

D'OraCa: Deep Learning-Based Classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer

Paolo Remagnino, Jian Han Lim, Sok Ching Cheong, 2021, MIUA.

Incorporating spatial information for microaneurysm detection in retinal images

Alicja R. Rudnicka, Christopher G. Owen, Andreas Hoppe, 2017 .

Retinal microvascular associations with cardiometabolic risk factors differ by diabetes status: results from the UK Biobank

R. A. Welikala, S. A. Barman, D. Strachan, 2022, Diabetologia.

QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size - An automated system for quantification of retinal vessels morphology

Muhammad Moazam Fraz, Alicja R. Rudnicka, Christopher G. Owen, 2015, Expert Syst. Appl..

Automated retinal vessel recognition and measurements on large datasets

Muhammad Moazam Fraz, Alicja R. Rudnicka, Christopher G. Owen, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy

T. Williamson, M. M. Fraza, A. Hoppea, 2015, Comput. Medical Imaging Graph..

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

D. Strachan, S. A. Barmana, M. Fraz, 2016, Comput. Biol. Medicine.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

D. Strachan, M. Fraz, A. Rudnicka, 2016, Comput. Biol. Medicine.

Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting

A. Rudnicka, C. Owen, M. Kolko, 2023, PloS one.

Retinal Vasculometry Associations with Cardiometabolic Risk Factors in the European Prospective Investigation of Cancer—Norfolk Study

D. Strachan, M. Fraz, A. Rudnicka, 2019, Ophthalmology.

Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort study

A. Rudnicka, R. Sofat, A. Warwick, 2023, BMJ Open Diabetes Research & Care.

Microaneurysm detection in retinal images using an ensemble classifier

Alicja R. Rudnicka, Christopher G. Owen, Sarah Barman, 2016, 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA).

Title: Artificial intelligence enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke

A. Rudnicka, K. Khaw, S. Hayat, 2022 .

DIFFERING MATCHED FILTER RESPONSIVITY FOR THE DETECTION OF PROLIFERATIVE DIABETIC RETINOPATHY

Jamshid Dehmeshki, Sarah Barman, R. A. Welikala, 2013 .