Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks
理解 Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks 一、摘要 1.提出了基於U-Net的卷積網絡。 2.在BRaTS2015上實驗。 二、Introduction 1.基於U-Net提出了2D全卷積網絡。 2.使用dice loss 損失函數。 3
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相關文章
- 1. Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks_2017
- 2. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
- 3. Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
- 4. Brain tumor segmentation with Deep Neural Networks
- 5. 肝臟分割 Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields
- 6. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
- 7. 3D MRI brain tumor segmentation using autoencoder regularization
- 8. R-FCN: Object Detection via Region-based Fully Convolutional Networks
- 9. Fully Convolutional Adaptation Networks for Semantic Segmentation
- 10. One-Pass Multi-task Convolutional Neural Networks for Efficient Brain Tumor Segmentation