A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
摘要： 1.通过将完全卷积神经网络（FC-NN）和条件随机场（CRF）集成在一个统一的框架中，得到一种新的脑肿瘤分割方法，以获得具有外观和空间一致性的分割结果。 2.步骤： 我们使用2D图像训练基于深度学习的分割模型 以下步骤中的块和图像切片： 1）使用图像块训练FCNN; 2）使用固定FCNN参数的图像切片训练CRF作为回归神经网络（CRF-RNN）; 3）使用图像切片微调FCNN和CRF-RN
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相关文章
- 1. 论文笔记：A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
- 2. Learning Contextual and Attentive Information for Brain Tumor Segmentation
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- 4. LEARNING VOLUMETRIC SEGMENTATION FOR LUNG TUMOR
- 5. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
- 6. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions论文笔记
- 7. Deep Convolutional Nets for Semantic Image Segmentation with Deep Gaussian CRFs
- 8. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
- 9. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
- 10. 论文阅读——A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation