The application of clustering and separability statistics on topographic data from the anterior eye assists in the classification of corneal disease or the identification of those at risk of angle-closure glaucoma. Imaging data from routinely available clinical instruments may be used and thus the method is transferable across existing imaging platforms.
- Uses the application of clustering, followed by separability testing, to generate 'isocontours' of anterior topographic clinical data from routinely available clinical instruments. Advantages include:
- Identifying corneal changes and the risk for corneal disease progression
- Identifying anterior chamber morphology changes to identify and phenotype different types of glaucoma
- Instrument agnostic and includes advantages such as: being non-invasive, easy and quick to acquire and readily interpretable
- Quick and easy to implement using techniques that currently exist in clinical practice and so will be highly accessible to clinicians
- Is accurate; it detects features that are not obvious to the naked eye and therefore not subject to human biases, fatigue, inexperience, education etc
- Is cost effective as it saves time. There are fewer images for clinicians to assess - the technology produces one simple, composite image from multiple images and has the potential to automate comparisons in follow up visits.
- Simplifying the detection of corneal ectatic disease in at-risk individuals
- Assisting in screening and predicting development of corneal complications following corneal surgery, including commonly-performed refractive surgery
- Improving the characterisation of anterior eye-morphology that makes an individual more susceptible to glaucoma
- Phenotyping different types of glaucoma to target and personalise a medical treatment approach
- Patent filing: provisional patent in preparation
- Start-up in development