Tag Archives: retinal imaging

Call for Participants in New Retinal Imaging Study

Principal Investigator, Dr Bashir Al-Diri and colleagues at the School of Computer Science are conducting a research project to collect 2D fundus images and 3D Optical Coherence Tomography (OCT) images using a fully automated user-friendly retinal-imaging camera (3D OCT-1 Maestro).

This study, titled ‘Automated Retinal Imaging Lab (ARIAL), will look towards finding and analysing new signs in the retinal vascular system photographed at the back of the eye, which might be changed due to disease. These signs can then be monitored and measured over time to detect signify disease progression.

OCT images are the most common techniques used for detecting eye diseases affecting the macula; OCT images are using in routine clinical practice and for diagnosis and monitoring diseases such as diabetes and high blood pressure as well as other systemic diseases.

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All images will be reviewed and stratified by a Consultant Ophthalmologist Surgeon. Any abnormality will be reported directly to you and your registered GP with clear advice on further action if needed.

For this study, we welcome everyone with or without any known eye disease or diagnosed with any chronic systemic diseases. OCT images and lifestyle data will be captured and collected every 6 months for the duration that you are available; each visit will take no longer than 30 minutes.

There has been no such dataset available for the research community in the past, so this project will be of great scientific interest.

Further information can be found here. To participate, please contact Dr Bashir Al-Diri: 

T. 01522 837111 / E. baldiri@lincoln.ac.uk 

Research presented at international computer vision conference

Two papers from academics in the School of Computer Science were presented at the world’s premier computer vision event.

The CVPR conference, which took place between June 24-27 in Ohio, is the highest-ranked venue in Computer Science.

According to Google Scholar Metrics, it is also the top publication venue in the field of computer vision and pattern recognition.

This year the University of Lincoln’s School of Computer Science was represented with two papers.

The first is ‘Gauss-Newton Deformable Part Models for Face Alignment in-the-Wild’ by Dr Georgios Tzimiropoulos and Maja Pantic.

Dr Tzimiropoulos’ research finds applications in face recognition, facial expression analysis and human behaviour understanding. In particular, prior to recognising someone’s identity or understanding his/her facial expressions, a computer program must be able to accurately detect and localise the facial parts like the mouth and the eyes, as well as track their deformable motion in video.

This very well-known computer vision problem, also known as face alignment, is a difficult one, especially when the faces to be analysed are captured in-the-wild, i.e. there is no control over illumination, image resolution, and head pose variations or occlusions. Dr Tzimiropoulos’ algorithm aims to address all of these challenging cases. A video with illustrative face tracking results can be found at: http://www.youtube.com/watch?v=MjCSWTFBrFg

The second paper is ‘A Bayesian Framework for the Local Configuration of Retinal Junctions’ by Touseef Qureshi, Professor Andrew Hunter and Dr Bashir Al-Diri.

This focusses on the development of a probabilistic system to accurately configure the broken vessels in retinal images.

Retinal images provide an internal view of the human eye (retina) that contains forests of blood vessels. These vessels provide useful information which can be used for diagnosing several cardiovascular and cerebrovascular diseases.

Computer-based automated extraction of significant features from the retinal vessels can help early diagnostics of these diseases.

The correct configuration of broken vessels into trees of arteries and veins is a prerequisite for extracting significant information from the vasculature.

Touseef said: “We achieve remarkable results in the initial experiments and intend to develop fully automated diagnostic system in future. Moreover, the proposed system can be optimized for other applications such as biometric security systems and road extraction using aerial images.”

Touseef outside the conference centre
Touseef outside the conference centre
Touseef with academic poster
Touseef with academic poster