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The Nigerian doctoral candidate fromBrunel University London’s Department of Computer Science demonstrated a new algorithm for OCT (Optical Coherence Tomography) equipment which can automatically segment images of the retina into distinct layers.

Having taken inspiration from the psychological concept of similarity, Bashir used the ideas of continuity and discontinuity to develop an OCT algorithm that can identify where one layer of the retina transitions to the next.

Speaking about his new diagnosis technique, Bashir, 29, said “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 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.” He said.

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Whilst doctors are currently able to identify the layers manually from OCT images, Bashir’s new technique automatically segments images of the retina, allowing specialists to spot abnormalities quicker and better track the progress of medication.

It’s therefore hoped the new technique, which can separate the retina into seven distinct layers, could improve the accuracy and speed of diagnosis, and help save the sight of patients by identifying damage earlier.