Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet
理解论文 Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet 一、摘要 1.提出了一种数据驱动方法用于肺肿瘤分割通过使用Recurrent 3D-DenseUNet。 2.使用大小为 256*256*8 的image-volumes with tumors 来训练网络。 3.还使用了数据驱动的自适应加权方法来区
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相关文章
- 1. LEARNING VOLUMETRIC SEGMENTATION FOR LUNG TUMOR
- 2. lung cancer detection
- 3. lung 分割论文
- 4. 3D MRI brain tumor segmentation using autoencoder regularization
- 5. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
- 6. Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks
- 7. TianCHi/LUNA16/Kaggle lung cancer肺结节数据集特征比较
- 8. [MICCAI2019]Integrating Cross-modality Hallucinated MRI with CT to Aid Mediastinal Lung Tumor
- 9. Brain tumor segmentation with Deep Neural Networks
- 10. Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks_2017