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Mar, 2022
ME-Net:用于脑肿瘤分割的多编码器网络框架
ME-Net: Multi-Encoder Net Framework for Brain Tumor Segmentation
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Wenbo Zhang, Guang Yang, He Huang, Weiji Yang, Xiaomei Xu...
TL;DR
该研究提出了一种用于进行脑肿瘤分割的多编码器模型及介绍了一种新的分类Dice损失函数,该方法可以降低特征提取难度,并显著提高模型性能,在验证集上能够与目前最先进的方法相媲美,在完整肿瘤,肿瘤核和增强肿瘤方面的Dice分数分别为0.70249,0.88267和0.73864。
Abstract
glioma
is the most common and aggressive brain tumor. Magnetic resonance imaging (
mri
) plays a vital role to evaluate tumors for the arrangement of tumor surgery and the treatment of subsequent procedures. Howeve
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