NMF for Quality Control of Multi-modal Retinal Images for Diagnosis of Diabetes Mellitus and Diabetic Retinopathy
Authors:
- 8 June 2022
- book chapter
- Published by Springer Nature
- p. 343-356
Abstract
No abstract availableKeywords
This publication has 12 references indexed in Scilit:
- Optical Coherence Tomography Angiography in Type 1 Diabetes Mellitus. Report 4: Glycated HaemoglobinDiagnostics, 2021
- Optical Coherence Tomography Angiography in Type 1 Diabetes Mellitus. Report 1: Diabetic RetinopathyTranslational Vision Science & Technology, 2020
- Re-epithelialization and immune cell behaviour in an ex vivo human skin modelScientific Reports, 2020
- Evaluation of microvascular changes in the perifoveal vascular network using optical coherence tomography angiography (OCTA) in type I diabetes mellitus: a large scale prospective trialBMC Medical Imaging, 2019
- Artificial intelligence for diabetic retinopathy screening: a reviewEye, 2019
- Fast and Robust Recursive Algorithmsfor Separable Nonnegative Matrix FactorizationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
- Convex and Semi-Nonnegative Matrix FactorizationsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2008
- Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysisBioinformatics, 2007
- Type 1 diabetesThe Lancet, 2006
- Learning the parts of objects by non-negative matrix factorizationNature, 1999