Utilizing SGANs for generating synthetic images of pterygium: training future optometrists and ophthalmologists

Che Azemin, Mohd Zulfaezal and Mohd Tamrin, Mohd Izzuddin and Hilmi, Mohd Radzi and Mohd Kamal, Khairidzan (2023) Utilizing SGANs for generating synthetic images of pterygium: training future optometrists and ophthalmologists. In: 4th Optometry Scientific Conference, 12-13 August 2023, Bangi, Selangor. (Unpublished)

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Abstract

Pterygium, an ocular surface disorder, poses diagnostic challenges for optometrists and ophthalmologists. We propose using Style-Generative Adversarial Networks (SGANs) to generate synthetic pterygium images for training purposes. A training dataset of 68 pterygium images collected during routine clinical examinations was used. Fréchet inception distance (FID) was employed to evaluate the similarity between the synthetic and original images. FID analysis revealed that the synthetic images closely resemble the original pterygium images, suggesting a high degree of similarity. This indicates the potential of SGANs in generating realistic pterygium images. The successful generation of synthetic pterygium images using SGANs provides a valuable tool for training future optometrists and ophthalmologists in pterygium diagnosis and grading. By expanding the availability of diverse pterygium images, trainees can enhance their skills and proficiency. The use of synthetic images overcomes limitations associated with obtaining a sufficient number of real pterygium images. Additionally, the availability of a large dataset of synthetic images enables the development of advanced machine learning algorithms and computer-assisted diagnostic tools, improving the accuracy and efficiency of pterygium grading. SGAN-generated images have the potential to standardize and control the training process, leading to improved patient care and management of pterygium.

Item Type:	Proceeding Paper (Other)
Uncontrolled Keywords:	Pterygium, Generative AI, Style-Generative Adversarial Network, Fréchet inception distance
Subjects:	R Medicine > R Medicine (General) T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Allied Health Sciences Kulliyyah of Allied Health Sciences > Department of Optometry and Visual Science Kulliyyah of Medicine Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Dr. Mohd Zulfaezal Che Azemin
Date Deposited:	19 Dec 2023 09:16
Last Modified:	31 Jan 2024 16:46
URI:	http://irep.iium.edu.my/id/eprint/108839

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