SVP Detection Using Machine Learning

This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.

Inclusion Criteria:Patients aged ≥18 years with presumed normal ICP undergoing routine dilated OCT scans.Patients undergoing a LP or continuous ICP monitoring with implanted transcranial pressure transducer devices at in- or out-patient neurology, neurosurgery or neuro-ophthalmology services.Exclusion Criteria:Glaucoma diagnosis or glaucoma suspects in either eye.Bilateral restricted fundal view, e.g. advanced bilateral cataracts.Bilateral retinal vein or artery occlusion.