Towards radiologist-level cancer risk assessment in CT lung screening using deep learning

5 Apr 2018Stojan TrajanovskiDimitrios MavroeidisChristine Leon SwisherBinyam Gebrekidan GebreBastiaan S. VeelingRafael WiemkerTobias KlinderAmir TahmasebiShawn M. RegisChristoph WaldBrady J. McKeeSebastian FlackeHeber MacMahonHomer Pien

Importance: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and it has been recently demonstrated that low-dose computed tomography (CT) screening of the chest can significantly reduce this death rate. Objective: To compare the performance of a deep learning model to state-of-the-art automated algorithms and radiologists as well as assessing the robustness of the algorithm in heterogeneous datasets... (read more)

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