Lung Cancer Nodule Detection Using Algorithm.
Principal Investigator
Name
MUHAMMAD UMAIR
Degrees
Bacholer
Institution
NED UNIVERSITY
Position Title
Engineer
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-688
Initial CDAS Request Approval
Jul 7, 2020
Title
Lung Cancer Nodule Detection Using Algorithm.
Summary
Lung cancer is the leading cause of cancer-related deaths worldwide, and early detection of lung cancer using low-dose computed tomography (CT) can prevent millions of patients from being killed each year. However, reading millions of CT scans is a heavy burden for radiologists. Computer-aided detection will help radiologists better detect nodules and easily obtain quantitative features such as nodule size and likelihood of malignancy. The National Lung Screening Trial (NLST) contains LDCT images for patients with lung cancers and with benign nodules. We plan to use these images to enhance our model to more accurately detect lung nodules from LDCT images.
Aims
- Develop a model for detecting and locating nodules.
- Develop a model to estimate the nodular malignancy and lung-RADS classification.
Collaborators
None