多尺度决策工具包 机器学习与偏微分方程融合的多尺度医学影像分割模型
Introduction
我们设计了一个深度主动轮廓网络(DACN)的新框架,它将主动轮廓模型(凸化的Chan-Vese模型)集成到CNN网络(DenseUNet)中。 模型能够利用主动轮廓模型的优势来精确检测物体的边界,并使用CNN网络自动学习主动轮廓模型的初始化和参数,以通过端到端的差分方式进行训练。在两个公共数据集上的实验结果表明,DACN模型具有精确提取物体边界轮廓的能力。
Publications
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Credits
- MoZhang zhangmo007@pku.edu.cn Contributor
Center for Data Science, Peking University, China
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Summary
Accession | BT007199 |
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Tool Type | Application |
Category | Image analysis |
Platforms | Linux/Unix |
Technologies | Python3 |
User Interface | Terminal Command Line |
Latest Release | 1.0 (June 2, 2021) |
Download Count | 36 |
Submitted By | bin dong |
Fundings
This work was supported by National Key R&D Program of China (No.2018YFC0910700)