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Table 8 Evaluation of all the deep learning models for brain tumor classification using the Gazi Brains 2020 Dataset. It can be observed that the data augmentation using the StyleGANv2-ADA GAN model achieves the best overall accuracy. The accuracy given here is the average of 5-fold training. Data Augmentation A = 50% is the parameter that shows how much training data in each fold is augmented and appended only to the train data

From: Development of brain tumor radiogenomic classification using GAN-based augmentation of MRI slices in the newly released gazi brains dataset

Models

Metrics

No Aug.

Traditional Aug.

StyleGANv2-ADA A = 50%

InceptionV3

Acc.

0.9492

0.9468

0.9936

DenseNet201

Acc.

0.9484

0.9603

0.9928

MobileNetV2

Acc.

0.9349

0.9619

0.9928

Xception

Acc.

0.9524

0.9563

0.9928

EfficientNetV2S

Acc.

0.946

0.9611

0.9936

ViT-Linformer

Acc.

0.7408

0.6573

0.6768

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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