Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge
Kingsley Kuan
Mathieu Ravaut
Gaurav Manek
Huiling Chen
Jie Lin
Babar Nazir
Cen Chen
T. C. Howe
Zengfeng Zeng
V. Chandrasekhar

Abstract
We present a deep learning framework for computer-aided lung cancer diagnosis. Our multi-stage framework detects nodules in 3D lung CAT scans, determines if each nodule is malignant, and finally assigns a cancer probability based on these results. We discuss the challenges and advantages of our framework. In the Kaggle Data Science Bowl 2017, our framework ranked 41st out of 1972 teams.
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