Lung cancer case prioritization tool with automated CT scan classification

Principal Investigator

Name
Ramune Dauksaite

Degrees
MSc, LLB

Institution
Birkbeck College, University of London

Position Title
Student

Email
rdauks01@mail.bbk.ac.uk

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-483

Initial CDAS Request Approval
Feb 19, 2019

Title
Lung cancer case prioritization tool with automated CT scan classification

Summary
Automated lung cancer case prioritisation software, which classifies CT lung scans to a reasonable accuracy for the purpose of case prioritisation. With staff and funding resources frequently being in deficit in health sectors, this tool would act as an aid for case prioritisation by indicating which CT scans represent a possible cancer case and should be reviewed first and which appear to represent healthy lungs and can be reviewed after high priority cases are addressed. The tool would reduce the time required to carry out manual case prioritisation and increase the efficiency of case processing.

Aims

- Working automated case prioritisation software, which classifies CT lung scans to a reasonable accuracy for the purpose of case prioritisation

Collaborators

N/A