《Deep learning with non-medical training used for chest pathology identification》論文解讀
該篇論文的主旨： 利用CNN網絡在非醫學圖像數據集上進行訓練，然後用93張醫學圖像進行測試，並利用AUC的面積進行衡量右肺胸腔積液檢測，心臟肥大和健康和有病的圖像分類問題。作者提出這是史無前例的利用非醫學圖像來訓練，但是模型在醫學圖像上依然通用的方法。 驗證深度學習CNNs方法在胸片圖像數據上的病理檢測的效果。 在訓練ImageNet圖像分類的網絡結構圖 以ImageNet中的數據集作爲輸入，分爲
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相關文章
- 1. 【論文閱讀筆記】CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
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- 3. [論文解讀]Towards Improved Testing For Deep Learning
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