Thakoor Kaveri A

Tian Ye, Sharma Anurag, Mehta Shubh, Kaushal Shubham, Liebmann Jeffrey M, Cioffi George A et al.

A deep learning model predicted ophthalmologist-fixated regions on glaucoma OCT reports. This could guide clinicians to key areas, aiding diagnosis and education for early detection of vision loss.

Hood Donald C, La Bruna Sol, Tsamis Emmanouil, Thakoor Kaveri A, Rai Anvit, Leshno Ari et al.

This study developed a model to differentiate glaucoma from common OCT p-map artifacts caused by normal anatomical variations, improving OCT-based glaucoma detection for clinical decisions, research, screening, and AI development.

Thakoor Kaveri A, Li Xinhui, Tsamis Emmanouil, Zemborain Zane Z, De Moraes Carlos Gustavo, Sajda Paul et al.

This study found data augmentation and confident image training improve CNN glaucoma detection from OCT. Consistent reference standards are crucial for optimal performance and clinical deployment.

Tsamis Emmanouil, Bommakanti Nikhil K, Sun Ashley, Thakoor Kaveri A, De Moraes Carlos Gustavo, Hood Donald C

This study developed an automated method to compare abnormal OCT and visual field regions in early glaucoma. It found specific criteria (OCT <10%, VF <5%) effectively identify structure-function agreement, reducing subjectivity in diagnosis.