Binary Classification of Liver Sides Roughness in Ultrasound Images Using Transformer and CNN Models with StyleGAN3 Data Augmentation

Norihiro KOIZUMI

doi:10.1007/s11548-025-03373-6

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Binary Classification of Liver Sides Roughness in Ultrasound Images Using Transformer and CNN Models with StyleGAN3 Data Augmentation

ジャーナル論文 - rm_published_papers: International Conference Proceedings

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Binary Classification of Liver Sides Roughness in Ultrasound Images Using Transformer and CNN Models with StyleGAN3 Data Augmentation

Norihiro KOIZUMI

Proc. of 39th International Congress and Exhibition on computer assisted radiology and surgery (CARS 2024), International Journal of Computer Assisted Radiology and Surgery (IJCARS), Vol.20(Suppl 1), ページS44-S45

18/06/2025

DOI: https://doi.org/10.1007/s11548-025-03373-6

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タイトル: Binary Classification of Liver Sides Roughness in Ultrasound Images Using Transformer and CNN Models with StyleGAN3 Data Augmentation
作成者 – 役職なし: Norihiro KOIZUMI
出版物に関する詳細: Proc. of 39th International Congress and Exhibition on computer assisted radiology and surgery (CARS 2024), International Journal of Computer Assisted Radiology and Surgery (IJCARS), Vol.20(Suppl 1), ページS44-S45
ID: 991002579066807421
組織: The University of Electro-Communications
言語: 英語
資料タイプ: ジャーナル論文
リソースのサブタイプ: rm_published_papers: International Conference Proceedings