Multi-task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein
Artery/Vein Classification 論文鏈接 1. 期刊 MICCAI 2019 2. 亮點 使用illumination correction (IC)和vessel enhancement (VE)增強數據，並和原始數據一起作爲網絡的輸入 在網絡輸出端，利用multi-task思想將輸出分爲兩個分支，其中一個分割血管，另外一個分割動靜脈 在multi-task
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相關文章
- 1. 《Dense Residual Network for Retinal Vessel Segmentation》
- 2. 論文閱讀——Multi-task Neural Networks with Spatial Activation for RVS and Artery/Vein Classification
- 3. 《Dual Encoding U-Net for Retinal Vessel Segmentation》閱讀筆記-MICCAI2019
- 4. Illumination correction by dehazing for retinal vessel segmentation
- 5. 論文筆記：Exploring Neural Networks with Activation Atlases
- 6. Brain tumor segmentation with Deep Neural Networks
- 7. 《Unsupervised Ensemble Strategy for Retinal Vessel Segmentation》--閱讀筆記-MICCAI2019
- 8. MS-NFN Model for Retinal Vessel Segmentation（血管分割）
- 9. 論文閱讀——Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation
- 10. 論文閱讀——A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation