RSSNI - Seminar: Jonathan Henderson, QUB, on early detection of Glaucoma.

Date: Wednesday 24 January 2024, 1.00PM
Location: QUB in-person and online with MS Teams
On-line with MS Teams software and the Peter Froggatt Centre Room 012 on the 3rd floor (main quadrangle, QUB). Campus Map provided.
Local Group Meeting


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  This is the first RSSNI seminar of 2024.
 
RSSNI - Talk on the 24th of January 2024 @1pm GMT

This is the first seminar of 2024. Jonathan Henderson, from Statistics in Queen's Belfast, will talk about the early detection of Glaucoma, a leading cause of blindness. This will be a hybrid event
with Jonathan in-person in the Peter Froggatt Centre (main quadrangle, QUB, room 012 on the 3rd. floor, campus map here) and on-line with MS Teams (link here).

Title:   Detecting Glaucoma Early: The Power of Fractal Measures and Change Point Detection in Retinal Assessment.

Abstract: 

Glaucoma, a leading cause of irreversible blindness, is characterized by the neurodegenerative loss of retinal ganglion cells (RGCs). While a definitive cure remains elusive, clinical techniques offer avenues to mitigate the impact, particularly when the condition is diagnosed early. Recent strides in Adaptive Optics confocal Scanning Laser Ophthalmoscopy are beginning to allow clinicians to visualize a small subset of the RGC population approaching the single cell resolution.  Distance-based metrics such as the nearest neighbour distance have been applied to these datasets, but have proven unreliable for early disease detection, due to point pattern heterogeneities and the presence of noise. To extract more reliable information from these observations, techniques from the field of point pattern analysis can be used. This study explores the potential of fractal geometry within the context of point patterns, showcasing their efficacy in identifying glaucoma in its incipient stages using rodent disease models. The use of these fractal measures is further considered in constructing model parameters for the disease process based on an approximate Bayesian computation algorithm. This allows for a change-point detection algorithm to be applied that can be used to identify regions of the retina at risk of future loss. This can be used to inform clinical practice through earlier diagnosis of disease and better prediction of therapeutic intervention efficacy.

All Welcome !

Gilbert MacKenzie &
Felicity Lamrock
RSSNI


See recorded talks here.
See write-ups of talks here.
 
Jonathan Henderson, Statistics, QUB, NI, UK.
 
Contact Gilbert MacKenzie RSSNI