Detection/Segmentation of lung cancer and more with deep learning

Principal Investigator

Name
Andy Song

Degrees
M.S.

Institution
Medipixel

Position Title
CEO

Email
andy.song@medipixel.io

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-376

Initial CDAS Request Approval
Nov 17, 2017

Title
Detection/Segmentation of lung cancer and more with deep learning

Summary
In this project, we're trying to detect lung cancer in lung CT, and perform segmentation of the nodule region. NLST datasets will be used as training/testset for our detection model. The second step will be to detect other diseases such as emphysema, PAH, etc. by annotating those anatomical structures, and training them for the model.

Aims

1. Determine if deep learning algorithm detects nodules accurately in low dose lung CT
2. Determine if our segmentation model performs segmentation well enough on nodules in low dose lung CT
3. Determine if deep learning algorithm classifies disease such as emphysema, and pulmonary arterial hypertension accurately.

Collaborators

Jay Lee, Medipixel
Hyungkyu Kim, Medipixel