Lung Nodule Detection

Principal Investigator

Name
Asma Alkhaldi

Degrees
B.Sc

Institution
Saudi Data and Artificial Intelligence Authority (SDAIA)

Position Title
Research Engineer

Email
aakhaldi@sdaia.gov.sa

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-896

Initial CDAS Request Approval
Mar 30, 2022

Title
Lung Nodule Detection

Summary
The project is about detecting the lung nodules using deep learning. It’s mainly about viewing CT lung and automatically highlight nodules which saves time of radiologist, pulmonologist, thoracic surgeon in nodule detection and improve the accuracy of the detection. In terms of radiologist performance, it was noted that AI model could improve the performance and help especially in detecting small lung nodules, <5 mm in size, which are often easily overlooked by visual inspection alone. Thus, AI model helps not only to reduce the burden of work on radiologists, and subsequently fatigue-related errors of judgement, but to improve detection of nodules particularly in the early stages of lung cancer, which are more likely to be missed.

Aims

Our aim of this project is to provide physicians with the diagnostic confidence and to alleviate some of the manual effort required of physicians/ radiologist reviewing many CT scans. This also would contribute in reducing their burden of work, optimizing hospital operational workflow, and providing more time to develop a high-quality physician-patient relationship.
Enhancing the radiologist's workflow with AI model can make the detection more cost-effective and feasible in countries where there is a shortage of senior radiologists.

Collaborators

Collaborators are:
1- Abdullah Almansour
2- Rawan Alyahya
3- Hanan Aldossari