Autonomous Grading Of Dynamic Blood Vessel Markers In The Eye Using Deep Learning

Project Member(s): Golzan, M.

Funding or Partner Organisation: Google LLC (Research Scholar Program)
Google LLC (Research Scholar Program)

Start year: 2021

Summary: This project aims to develop a deep learning model that will objectively grade spontaneous retinal venous pulsations

Publications:

Bae, HY, Saberi, M, Shariflou, S, Kalloniatis, M, Phu, J, Agar, A, Cheraghian, A & Golzan, SM 1970, 'Enhancing Glaucoma Diagnosis through Vision-Language Models and Large Language Model Descriptions', 2024 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2024 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 198-205.
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Sheng, H, Yu, X, Wang, F, Khan, MDW, Weng, H, Shariflou, S & Golzan, SM 1970, 'Autonomous Stabilization of Retinal Videos for Streamlining Assessment of Spontaneous Venous Pulsations', 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, pp. 1-4.
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Panahi, A, Rezaee, A, Hajati, F, Shariflou, S, Agar, A & Golzan, SM, 'Autonomous assessment of spontaneous retinal venous pulsations in fundus videos using a deep learning framework', Scientific Reports, vol. 13, no. 1.
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FOR Codes: Ophthalmology and Optometry, Artificial Intelligence and Image Processing, Medical Instruments, Deep learning

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.