One-Pass Multi-task Convolutional Neural Networks for Efficient Brain Tumor Segmentation
method: 首先：用三個網絡來訓練，分別針對comlete區域，core區域，和enhancing區域（使用網絡OM-net） 1.使用隨機採樣從MRI大腦圖像中採塊，訓練，分類器分爲5類，最後測試的時候直接測出complete區域，得到粗分割，並且使用腐蝕的方法，平滑complete，消除一些假陰性 2.訓練樣本是從complete中提取，訓練，分類，我的理解應該是分爲core裏面的3類，得
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相關文章
- 1. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
- 2. Brain tumor segmentation with Deep Neural Networks
- 3. Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks
- 4. Pruning Convolutional Neural Networks For Resource Efficient Inference
- 5. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- 6. Paper Reading：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- 7. EffNet: An Efficient Structure for Convolutional Neural Networks
- 8. Learning Contextual and Attentive Information for Brain Tumor Segmentation
- 9. 《Constrained Convolutional Neural Networks for Weakly Supervised Segmentation》翻譯
- 10. LEARNING VOLUMETRIC SEGMENTATION FOR LUNG TUMOR