Contributions by role
Contributions by subject area
Sufian A Badawi
Summary
Sufian has awarded a Ph.D. from the National University of Sciences and Technology at 27-Aug-2020. Involved in research and academia for the last six years. My research topic is segmentation, classification, and morphometric analysis for retinal vasculature, mainly used deep learning, advanced digital image processing, and machine learning to early diagnose hypertensive retinopathy eye disease indicators.
Research Achievements
1. Proposed a hybrid method for automatic detection and grading of hypertensive retinopathy in retinal images.
2. Developed new approaches for morphometric analysis of retinal vessels for measuring:
a. The vessel tortuosity.
b. The Arteriovenous ratio (AVR).
c. The severity-level of hypertensive retinopathy.
3. Achieved Artery/Vein classification of retinal vasculature. The method performs artery vein (AV) classification directly from the original retinal images, eliminating the preliminary step of retinal blood vessel delineation.
4. Optimized unsupervised retinal vessel segmentation.
5. Prepared a large scale labeled retinal dataset(s) with ground truths reviewed by two ophthalmologists and used in proposed methods, called retinal vessel morphometry (RVM) dataset that is made available publicly
He possesses a set of international certifications (black belt six sigma, TOGAF 9.1 enterprise architect, ISO27001 team lead auditor, ORACLE internet application developer, and JAVA certified developer).