Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge

• DOI: 10.48550/arxiv.1705.09435
• Publication Date: 2017-01-01
• Authors: Kingsley Kuan; Mathieu Ravaut; Gaurav Manek; Huiling Chen; Jie Lin; Babar Nazir; Cen Chen; Tse Chiang Howe; Zeng Zeng; Vijay Chandrasekhar
• Keywords: FOS: Computer and information sciences; Computer Vision and Pattern Recognition (cs.CV); Computer Science - Computer Vision and Pattern Recognition; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 3. Good health

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