Similar patch image retreival for cancer diagnosis

Principal Investigator

Name
Moti Moravia

Degrees
M.E

Institution
Datability

Position Title
CTO

Email
moti@datability-tech.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-954

Initial CDAS Request Approval
Sep 6, 2022

Title
Similar patch image retreival for cancer diagnosis

Summary
Research the ability to retrieve similar image patches from a query image patch. The user will mark an ROI (Region of interest) around the desired zone in the image. The AI algorithm will analyze the patch and retrieve the most similar image patches from other CT scans. In case the doctor has marked an anomaly (for example lung nodule), the retrieved patches suppose to include the same anomaly as a reference for the doctor to have the most precise diagnosis. In case no anomaly is present in the patch, the system retrieves the most similar patches with no anomaly present. Clinical data is to be analyzed to research the relevancy and correlation with this method.

Aims

* Successfully retrieve similar image patches to the query image patch.
* Check the correlation between the retrieved images and the clinical data for each patient.

Collaborators

NAN