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.提出了基于U-Net的卷积网络。 2.在BRaTS2015上实验。 二、Introduction 1.基于U-Net提出了2D全卷积网络。 2.使用dice loss 损失函数。 3
相关文章
- 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. 肝脏分割 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
- 更多相关文章...
- • W3C RDF and OWL 活动 - W3C 教程
- • XSL-FO table-and-caption 对象 - XSL-FO 教程
- • RxJava操作符（七）Conditional and Boolean
- • Flink 数据传输及反压详解
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 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. 肝脏分割 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