用卷积滤波器matlab代码-KiU-Net-pytorch:用于图像分割的KiU-Net的官方Pytorch编码-MICCAI2020(口服

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用卷积滤波器matlab代码KiU-Net-Pytorch | | | 在MICCAI 2020及其上发表的论文的官方Pytorch编码 期刊扩展: 关于此仓库: 此存储库托管以下网络的代码: KiU-Net 2D KiU-Net 3D Res-KiU网 致密网 它还具有组织用于通用2D图像分割和BraTS,LiTS数据集的3D体积分割的数据加载器; 便于对医学图像和体积分割算法进行基准测试。 介绍 在通用的“编码器-解码器”体系结构中,编码器的最初几个块学习数据的低级特征,而后面的块学习高级数据。 最终,编码器学会了将数据映射到较低维度(在空间意义上)。 随着网络深度的增加,接收场的大小也限制了网络将更多的精力放在更高层次的功能上。 在我们提出的体系结构中,我们引入了Ki-Net,其中我们使用了过完整的表示形式,这限制了接收域的增加。 这是通过对编码器的体系结构进行简单的更改来完成的,其中最大池化被上采样替代。 这有助于深层过滤器将更多的注意力集中在低级细节上,从而有助于细分。 当使用U-Net增强时,该网络称为KiU-Net,在分割较小的解剖标志和模糊的噪声边界的情况下,可以带来显

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