A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI
Abstract：磁共振成像數據集的自動心臟分割是及時診斷和管理心臟病變的重要步驟。我們建議通過應用deepFCN架構來解決自動左心室和右心室分割的問題。我們的模型在整個圖像輸入和ground-truth的單一學習階段進行端到端的高效訓練，以便在每個像素處進行推理。據我們所知，這是完全卷積神經網絡結構的第一個應用，用於CMRI中的像素標記。此外，我們的模型速度快，可以利用商品計算資源（如GPU）實
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相關文章
- 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. 論文閱讀筆記（五十四）：V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation