A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI
Abstract：磁共振成像数据集的自动心脏分割是及时诊断和管理心脏病变的重要步骤。我们建议通过应用deepFCN架构来解决自动左心室和右心室分割的问题。我们的模型在整个图像输入和ground-truth的单一学习阶段进行端到端的高效训练，以便在每个像素处进行推理。据我们所知，这是完全卷积神经网络结构的第一个应用，用于CMRI中的像素标记。此外，我们的模型速度快，可以利用商品计算资源（如GPU）实
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相关文章
- 1. Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network.
- 2. Transposed convolution & Fully Convolutional Neural Network
- 3. Fully Convolutional Adaptation Networks for Semantic Segmentation
- 4. A New Hand Segmentation Method Based on Fully Convolutional Network
- 5. Multi-task Fully Convolutional Network for Brain Tumour Segmentation
- 6. Fully Convolutional Networks for Semantic Segmentation
- 7. Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
- 8. 3d fully convolutional network for vehicle detection in point cloud
- 9. FCN—— Fully Convolutional Networks for Semantic Segmentation
- 10. 论文阅读笔记（五十四）：V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation