Filtered 1:1 synthetic MRI augmentation improved MobileViTV2 tumour classification accuracy by 1.02% on BRISC 2025 while providing no benefit to random forest and non-significant gains for CNN.
GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification,
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Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025
Filtered 1:1 synthetic MRI augmentation improved MobileViTV2 tumour classification accuracy by 1.02% on BRISC 2025 while providing no benefit to random forest and non-significant gains for CNN.