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September 5, 2025Scientific ReportsOpen Access

Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures

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This approach demonstrates improved glioma semantic segmentation using U-Net and pre-trained networks, suggesting better treatment decisions.

Trained ResNet-U-Net shows the highest accuracy for necrotic and active tumor regions in glioma.
Assessments of segmentation performance were based on accuracy and intersection over union metrics.
Utilization of pre-trained Backbone U-Net networks like ResNet, Inception, and VGG improved segmentation outcomes.
The study's framework enables valuable semantic information extraction for glioma management.

Amir Khorasani (2025) studied this question.

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This approach demonstrates improved glioma semantic segmentation using U-Net and pre-trained networks, suggesting better treatment decisions.