Meet Bashir Isa Dodo, the Nigerian-born computer genius uncovering new method for diagnosing damage to human eye

Mohammed Awal Aug 6, 2020 at 12:00pm

August 06, 2020 at 12:00 pm | Tech & Innovation

Mohammed Awal

Mohammed Awal

August 06, 2020 at 12:00 pm | Tech & Innovation

Photo source: UMYU/LinkedIn/Safiyanu Yakubu Source: UGC The technique reportedly can separate the retina into seven distinct layers, which could improve the accuracy and speed of diagnosis.

Bashir Isa Dodo is a Nigerian-born computer genius. A doctoral degree candidate at Brunel University London, Dodo was adjudged the winner of the University’s Dean Prize for Impact and Innovation 2020.

The Nigerian, whose public profile labeled him as a computer scientist and a former assistant lecturer in the department of mathematics and computer science at Umaru Musa Yar’adua University in Northern region, also picked the Vice Chancellor’s Prize for Doctoral Research.

Dodo’s academic astuteness came in the limelight when his research paper on a new method for identifying and diagnosing damage to the human retina was awarded the ‘Best Student Paper’ at the BIOIMAGING 2018 conference in Portugal.

A receiver of B.Sc. degree (Hons.) in software engineering and the M.Sc. degree in computer systems engineering (software systems) from the University of East London, U.K., in 2011 and 2013, respectively, Dodo demonstrated at the conference the new algorithm for OCT (Optical Coherence Tomography) equipment which can automatically segment images of the retina into distinct layers, according to reports.

The technique reportedly can separate the retina into seven distinct layers, which could improve the accuracy and speed of diagnosis.

“Layer segmentation is one of the early processes of OCT retina image analysis, and already plays an important role in clinics,” Dodo said of his technique. 

For instance, the thickness profile of the Retinal Nerve Fibre Layer – which can be calculated directly from the segment layer – he said is used in the diagnosis of glaucoma, which is one of the most common causes of sight-loss world-wide.

“Automatically segmenting the layers could provide critical information for abnormality detection by comparing them to the average population, and monitoring the progress of disease against previous scans,” Dodo said.

Dodo is currently pursuing a Ph.D. degree with the Department of Computer Science, Brunel University London, the U.K, and his research interests include software engineering, motion detection, computer vision, image processing, medical image analysis, and big data analytics.  

Most viewed

Conversations

Must Read