Deep Learning Is Effective for Classifying Normal versus Age-Related Macular Degeneration OCT Images
深度學習在老年性黃斑中的分類應用 一、方法與結果總結 1.研究方法 儀器： Heidelberg Spectralis 從OCT數據庫中獲取圖像並鏈接至EMR（電子病歷）中，需要注意的是，我們只取兩類對象的圖片：健康與AMD（老年性黃斑患者），而且每個患者的OCT斷層圖像只取中心的11張圖像。通過隨機數據集訓練網絡，最終從患者角度、黃斑OCT角度、圖像角度建立ROC曲線。 實驗結果的好壞由ROC曲
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相關文章
- 1. Deep Learning Is Effective for Classifying Normal versus Age-Related Macular Degeneration OCT Images
- 2. 【論文筆記】（三）Deep Learning Is Effective for Classifying Normal versus Age-Related Macular Degeneration
- 3. Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning
- 4. OCT病竈分割論文泛讀
- 5. What are some good books/papers for learning deep learning?
- 6. A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions
- 7. What is Deep learning?
- 8. Wide&Deep versus DeepFM
- 9. （轉）WHY DEEP LEARNING IS SUDDENLY CHANGING YOUR LIFE
- 10. A Vision for Making Deep Learning Simple