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PERBANDINGAN PERFORMA U-NET DAN SWIN UNETR PADA SEGMENTASI CITRA MRI TUMOR OTAK
Brain tumors require rapid and accurate diagnosis, while manual segmentation of Magnetic Resonance Imaging (MRI) scans is time-consuming and highly dependent on expert knowledge. This study compares the performance of two deep learning architectures for brain tumor segmentation, namely 3D U-Net and Swin UNETR, trained and validated using the BraTS dataset and evaluated on unseen cases. Model pe…
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- xvi, 138 hlm.; ilus.; tab.; 29 cm
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- T1900062025
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