A hybrid machine learning approach using LBP descriptor and PCA for age-related macular degeneration classification in OCTA images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • External authors:
  • Abdullah Alfahaid
  • Pearse A Keane
  • Hagar Khalid
  • Nikolas Pontikos
  • Konstantinos Balaskas


We propose a novel hybrid machine learning approach for
age-related macular degeneration (AMD) classification to support the
automated analysis of images captured by optical coherence tomography
angiography (OCTA). The algorithm uses a Rotation Invariant Uniform
Local Binary Patterns (LBP) descriptor to capture local texture patterns
associated with AMD and Principal Component Analysis (PCA)
to decorrelate texture features. The analysis is performed on the entire
image without targeting any particular area. The study focuses on
four distinct groups, namely, healthy; neovascular AMD (an advanced
stage of AMD associated with choroidal neovascularisation (CNV)); nonneovascular AMD (AMD without the presence of CNV) and secondary
CNV (CNV due to retinal pathology other than AMD). Validation sets
were created using a Stratified K-Folds Cross-Validation strategy for limiting
the overfitting problem. The overall performance was estimated
based on the area under the Receiver Operating Characteristic (ROC)
curve (AUC). The classification was conducted as a binary classification
problem. The best performance achieved with the SVM classifier based
on the AUC score for: (i) healthy vs neovascular AMD was 100%, (ii)
neovascular AMD vs non-neovascular AMD was 85%; (iii) CNV (neovascular
AMD plus secondary CNV) vs non-neovascular AMD was 83%.

Bibliographical metadata

Original languageEnglish
Title of host publicationMedical Image Understanding and Analysis - 23rd Conference, MIUA 2019, Proceedings
EditorsYalin Zheng, Bryan M. Williams, Ke Chen
Number of pages12
Publication statusPublished - 2020
Event23rd Conference in Medical Imaging, Understanding and Analysis -
Event duration: 24 Jul 201926 Jul 2019

Publication series

NameCommunications in Computer and Information Science
Volume1065 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference23rd Conference in Medical Imaging, Understanding and Analysis
Abbreviated titleMIUA 2019