A project for lung nodule detection
Principal Investigator
Name
Haoyue Peng
Degrees
M.E
Institution
Pingan Technology
Position Title
intern
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-524
Initial CDAS Request Approval
Jun 17, 2019
Title
A project for lung nodule detection
Summary
Lung cancer, causing 1.3 million deaths annually, is a leading cause of cancer death worldwide. Detection and treatment at an early stage are required to effectively overcome this burden. Computed tomography (CT) was recently adopted as a mass-screening tool for pulmonary cancer diagnosis, enabling rapid improvement in the ability to detect lung nodule early. And dections of lung nodule can be assisted by deep learning algorithm. Image features can be extracted efficiently by deep learning algorithm trained with big data, which help detect lung nodule of "fresh" CT. For our project, we aim to develop new methods and evaluate the methods for early lung cancer detection and survival prediction on the requested data set.
Aims
1) Verify the availability of different deep learning models on lung cancer prediction.
2) Develop deep learning network for detection of lung nodule and classification of lung cancer.
Collaborators
Lingyun Huang, Pingan Technology