Skip to Main Content
An official website of the United States government
Login Change: CDAS is now using the NIH Researcher Auth Service (RAS) to manage our existing login options. When logging into CDAS, you will be taken to RAS, where you can select your preferred login provider to access CDAS.

detecting, marking and classifying lung cancer in CT-Scans with deep learning algorithms

Principal Investigator

Name
Qasim Mohammad

Institution
Independent

Position Title
student

Email
doc.qasim@yahoo.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-378

Initial CDAS Request Approval
Dec 1, 2017

Title
detecting, marking and classifying lung cancer in CT-Scans with deep learning algorithms

Summary
We are trying to detect and mark lung cancer in CT-Scans. Having detected and marked successfully, we would like to classify lung cancer in subgroups. All this work is done with deep learning algorithms. NLST datasets will be used as trainingset for our neural network.

Aims

- create deep learning model to detect lung cancer in CT-Scans
- create deep learning model to mark lung cancer structures in CT-Scans
- help physicians to classify lung cancer in subgroups with deep learning model

Collaborators

Owais Mohammad (Klinikum Ludwigshafen, Germany)