Nigerian student develops new diagnosis for retina disease

A Nigerian student at the Brunel University, London, Mr. Bashir Dodo, has developed a new technique for identifying and diagnosing damage to the human retina.

A statement released by the Press Office of the university on Thursday described the technique as an algorithm for Optical Coherence Tomography equipment, which could automatically segment images of the retina into seven distinct layers.

The statement said that Dodo, currently a doctoral student at the institution’s Department of Computer Science, demonstrated the new algorithm at the BIOIMAGING 2018 Conference recently held in Portugal and was rewarded with the ‘Best Student Paper’ Award at the event.

It noted that Dodo, who seemed to have been inspired by the psychological concept of similarity, used the ideas of continuity and discontinuity to develop the algorithm.

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The university expressed the hope that apart from improving the accuracy and speed of diagnosis, the technique would help to save the sight of patients by identifying damage earlier.

Evidently giving a brief analysis of the new technique, Dodo was quoted as saying, “Layer segmentation is one of the early processes of OCT retina image analysis, and already plays an important role in clinics.

“For example, the thickness profile of the Retinal Nerve Fibre Layer – which can be calculated directly from the segment layer – is used in the diagnosis of glaucoma, which is one of the most common causes of sight loss worldwide.

“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.”

The statement stressed that while doctors were able to identify the layers manually from OCT images, Dodo’s new technique would automatically segment images of the retina, thereby allowing specialists to spot abnormalities quicker and better track the progress of medication.


News Reporter

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