Nigerian-born Bashir Isa Dodo could easily be classified as a computer genius for lack of a better word. He was classed as the winner of the University’s Dean Prize for Impact and Innovation 2020. He also won the “Best Student Paper” at the Bioimaging conference in Portugal for the development of a new algorithm that can separate the retina into seven individual layers to accelerate the diagnosis of diseases to the eye.
The Nigerian, a former assistant lecturer in the department of mathematics and computer science at Umaru Musa Yar’adua University in the Northern region of Nigeria, also picked the Vice Chancellor’s Prize for Doctoral Research.
Dodo’s academic prowess 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 targeting a Ph.D. degree from the Department of Computer Science, Brunel University London, his research interests include software engineering, motion detection, computer vision, image processing, medical image analysis, and big data analytics. His main research interests are in medical image analysis and video processing.
On receiving his recent award Mr. Bashir Isa Dodo said “It is with the jubilation of heart that I share the news of my award conferment, which by the way came with the following icing: Vice Chancellor’s prize for Doctoral research and Dean’s Prize for Innovation and Impact in Doctoral Research. My ability did not do it, rather prayers and well wishes. I thank my wife, children, family, and friends for the prayers well answered on my birthday, as one of the awards was on that same day. The Almighty has certainly answered. My profound gratitude to my supervisors, Dr Yongmin Li and Prof. Xiaohui Lui for their unwavering support and mentoring.”
An abstract from his work submitted for the award of Doctor of Philosophy and was awarded by Brunel University London reads :
Three out of the four leading eye diseases aﬀect the retina, causing irreversible blindness and various degrees of visual impairment. In the clinic, the eﬀects of these diseases and other cardiovascular disorders are attributed to structural changes in the retinal structures. These changes are evaluated using various imaging techniques such as fundus imaging and optical coherence tomography (OCT). Consequently, the analysis of these images has become vital for diagnosing various ocular diseases in modern ophthalmology. Many computer-aided diagnostic (CAD) methods have been proposed to aid with the analysis due to the complexity of the retinal structures, the tediousness of manual segmentation, and variation from diﬀerent specialists. Besides, the commercially available systems focus on only a few layers of the retina, even though recent researches in the ﬁeld of ophthalmology and neurology show that each layer might be aﬀected individually. The reasons mentioned earlier urge for eﬃcient intra-retinal layer segmentation methods. However, image artifacts such as speckle noise and inhomogeneity in pathological structures remain a challenge, with negative inﬂuence on the performance of segmentation algorithms.
This study investigates methods for image analysis, aiming to develop robust algorithms for segmenting retinal OCT images. Hence, this thesis presents four methods for extracting individual layer information from OCT to help with eye screening and management of various eye disorders, including glaucoma, diabetic retinopathy, age-related macular degeneration, among others. Distinctly, the ﬁrst method is a comprehensive and fully automated method for annotation of retinal layers in OCT images, which comprises of fuzzy histogram hyperbolization for weight reassignment within adjacency matrices and graph-cut (shortest path) to segment seven (7) layers across eight (8) boundaries of the retina. Second, prior knowledge of the retinal architecture derived from the gradient information is embedded into the level set method to segment seven (7) layers of the retina. This method starts by establishing a region of interest (ROI), and then the reﬁned gradient edges obtained from the ROI are used to initialize a level set function.
Then, the understanding of layer topology is used in constraining the evolution process towards the actual layer boundaries.
Bashir has presented his excellent works at various seminars, symposiums, and conferences. He was part of the local organizing committee of the 16th International Symposium on Intelligent Data Analysis (IDA 2017). Bashir’s publications have been cited in Research Gate with 489 Reads and 1 citation.
Bashir’s work has been featured in various media such as BBC World and TVC News. A dedicated, hardworking, and optimistic researcher, very passionate about a role in supporting learning. Bashir is always looking for the opportunity to impact the next generation of computer scientists. This is due to his strong belief in the importance of education in society, and the rewarding experience teaching provides.