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Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability

In this study, we leveraged StyleGAN 3 to synthesize high-fidelity images of pterygium, achieving significant strides in image realism as evidenced by low Fréchet Inception Distance (FID) scores. Our results demonstrate that StyleGAN 3 can intricately capture the textural nuances and vascular patter...

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Main Authors: Che Azemin, Mohd Zulfaezal, Mohd Tamrin, Mohd Izzuddin, Hilmi, Mohd Radzi, Mohd Kamal, Khairidzan
Format: Proceeding Paper
Language:English
English
English
Published: Association for Computing Machinery 2024
Subjects:
RE Ophthalmology
T Technology (General)
Online Access:http://irep.iium.edu.my/112492/2/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203.pdf
http://irep.iium.edu.my/112492/3/112492_ICSCA%202024%2013th%20International%20Conference%20on%20Software%20and%20Computer%20Applications.pdf
http://irep.iium.edu.my/112492/4/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203_Scopus.pdf
http://irep.iium.edu.my/112492/
https://dl.acm.org/doi/10.1145/3651781.3651810
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spelling my.iium.irep.1124922024-06-26T02:11:42Z http://irep.iium.edu.my/112492/ Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability Che Azemin, Mohd Zulfaezal Mohd Tamrin, Mohd Izzuddin Hilmi, Mohd Radzi Mohd Kamal, Khairidzan RE Ophthalmology T Technology (General) In this study, we leveraged StyleGAN 3 to synthesize high-fidelity images of pterygium, achieving significant strides in image realism as evidenced by low Fréchet Inception Distance (FID) scores. Our results demonstrate that StyleGAN 3 can intricately capture the textural nuances and vascular patterns distinctive to pterygium, with color tones and variations that closely mirror clinical photography. The generated images exhibit high equivariance to transformations, retaining their realism under various manipulations. Clinician reviews, expressed through confusion matrices, validated the authenticity of the synthetic images, although variations in individual assessments highlighted the challenges in differentiating between generated and real images. Ultimately, our findings confirm the efficacy of StyleGAN 3 in producing synthetic medical images that could potentially expand datasets for medical research and training, while also underscoring the necessity for diversity in training data and model tuning to achieve optimal realism. Association for Computing Machinery 2024-05-30 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/112492/2/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203.pdf application/pdf en http://irep.iium.edu.my/112492/3/112492_ICSCA%202024%2013th%20International%20Conference%20on%20Software%20and%20Computer%20Applications.pdf application/pdf en http://irep.iium.edu.my/112492/4/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203_Scopus.pdf Che Azemin, Mohd Zulfaezal and Mohd Tamrin, Mohd Izzuddin and Hilmi, Mohd Radzi and Mohd Kamal, Khairidzan (2024) Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability. In: 13th International Conference on Software and Computer Applications, ICSCA 2024, 1-3 Feb 2024, Bali, Indonesia. https://dl.acm.org/doi/10.1145/3651781.3651810 10.1145/3651781.3651810
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic RE Ophthalmology
T Technology (General)
spellingShingle RE Ophthalmology
T Technology (General)
Che Azemin, Mohd Zulfaezal
Mohd Tamrin, Mohd Izzuddin
Hilmi, Mohd Radzi
Mohd Kamal, Khairidzan
Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
description In this study, we leveraged StyleGAN 3 to synthesize high-fidelity images of pterygium, achieving significant strides in image realism as evidenced by low Fréchet Inception Distance (FID) scores. Our results demonstrate that StyleGAN 3 can intricately capture the textural nuances and vascular patterns distinctive to pterygium, with color tones and variations that closely mirror clinical photography. The generated images exhibit high equivariance to transformations, retaining their realism under various manipulations. Clinician reviews, expressed through confusion matrices, validated the authenticity of the synthetic images, although variations in individual assessments highlighted the challenges in differentiating between generated and real images. Ultimately, our findings confirm the efficacy of StyleGAN 3 in producing synthetic medical images that could potentially expand datasets for medical research and training, while also underscoring the necessity for diversity in training data and model tuning to achieve optimal realism.
format Proceeding Paper
author Che Azemin, Mohd Zulfaezal
Mohd Tamrin, Mohd Izzuddin
Hilmi, Mohd Radzi
Mohd Kamal, Khairidzan
author_facet Che Azemin, Mohd Zulfaezal
Mohd Tamrin, Mohd Izzuddin
Hilmi, Mohd Radzi
Mohd Kamal, Khairidzan
author_sort Che Azemin, Mohd Zulfaezal
title Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
title_short Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
title_full Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
title_fullStr Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
title_full_unstemmed Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability
title_sort assessing the efficacy of stylegan 3 in generating realistic medical images with limited data availability
publisher Association for Computing Machinery
publishDate 2024
url http://irep.iium.edu.my/112492/2/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203.pdf
http://irep.iium.edu.my/112492/3/112492_ICSCA%202024%2013th%20International%20Conference%20on%20Software%20and%20Computer%20Applications.pdf
http://irep.iium.edu.my/112492/4/112492_Assessing%20the%20efficacy%20of%20StyleGAN%203_Scopus.pdf
http://irep.iium.edu.my/112492/
https://dl.acm.org/doi/10.1145/3651781.3651810
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score 13.211869

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