Brain tumor classification using GAN-augmented data with autoencoders and Swin Transformers

Brain tumor classification using GAN-augmented data with autoencoders and Swin Transformers

IntroductionBrain tumor classification remains one of the most challenging tasks in medical image analysis, with diagnostic errors potentially leading to severe consequences. Existing methods often fail to fully exploit all relevant features, focusing on a limited set of deep features that may miss...

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Bibliographic Details
Main Authors: Abdullah Almuhaimeed, Anas Bilal, Abdulkareem Alzahrani, Malek Alrashidi, Mansoor Alghamdi, Raheem Sarwar
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Medicine
Subjects:
brain tumour classification
conditional GAN
synthetic data
Swin Transformer
autoencoders
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1635796/full
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https://www.frontiersin.org/articles/10.3389/fmed.2025.1635796/full

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