DeepLesion: Automated Deep Mining, Categorization and Detection of Significant RadiologyImageFinding
摘要：抽取、分割和大規模標註放射圖像數據是一項非常重要且有挑戰的問題。對醫學圖片設計有效的計算範例而言，這也是一個瓶頸。但大量的臨牀標註（通常結合疾病圖像的發現，並以箭頭、橫線、直徑、分割等標註）已經收集好，儲存在醫院的PACS中。在本文中，作者挖掘並獲取了一種主要類型的臨牀批註數據——在書籤圖像上批註的病竈直徑——通過無監督和有監督的深卷積神經網絡來學習一種有效的多類病竈檢測器(CNN)。數據從
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相關文章
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