Automatic Computer-aided Lung Cancer Diagnosis by Deep Learning
Principal Investigator
Name
Yin Wang
Degrees
Ph.D
Institution
Tongji University
Position Title
Professor
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-545
Initial CDAS Request Approval
Jul 29, 2019
Title
Automatic Computer-aided Lung Cancer Diagnosis by Deep Learning
Summary
Lung cancer is the leading cause of cancer death worldwide. Like other cancer, the best solution for lung cancer is early diagnosis and timely treatment. However, evaluate the malignancy of pulmonary nodules from CT scans is not a trivial task. Deep learning has shown advantages in many computer vision tasks including nodule detection and classification. Many recent publication also shows that with more data, deep learning algorithm tends to perform better. With the large amount of CT scans that NLST dataset provides, we hope to study how the amount of labeled CT scans can help deep learning algorithm to extract robust image features to perform both nodule detection and classification tasks, and develop new method for nodule detection and classification tasks.
Aims
1) To validate the effectiveness of different deep learning model on the task of lung nodule detection and ciassification.
2) To develop new deep learning network for detection of lung nodule and classification of lung cancer.
Collaborators
Baoxue Ge, Tongji University
Bingchen Zhao, Tongji University
Shouyu Chen, Tongji University
Siwei Yang, Tongji University