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Updated: Jul 16, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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深度学习驱动的脑瘤分类和细分使用非对比的MRI

Nan-Han Lu1,2, Yung-Hui Huang3, Kuo-Ying Liu4

  • 1Department of Radiology, E-DA Cancer Hospital, I-Shou University, No. 21, Yida Road, Jiao- Su Village, Yan-Chao District, Kaohsiung, 82445, Taiwan. leunanhan@seed.net.tw.

Scientific reports
|July 31, 2025
PubMed
概括

使用综合MRI扫描 (T1w,T2w和平均) 的深度学习模型显著提高了脑瘤诊断的准确性. 这种方法在分类中获得了98.3%的准确性,在细分中获得了0.937个子得分.

关键词:
人工智能的人工智能是人工智能.大脑MRI 脑部MRI 脑部卷积神经网络 (CNN) 是一种神经网络.深度学习是一种深度学习.完全卷积网络 (FCN) 是一个完全卷积网络.瘤的分类 瘤的分类瘤细分 瘤的细分

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