Virtual biopsy of pulmonary nodules
Principal Investigator
Name
Francesco Ciompi
Institution
Radboud University Medical Center
Position Title
Post-doc
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-164
Initial CDAS Request Approval
Sep 30, 2015
Title
Virtual biopsy of pulmonary nodules
Summary
In this project, we aim at designing a computer model able to automatically assess malignancy of a detected pulmonary nodule in a CT scan.
NLST data will be used to train the computer model by extracting information from baseline and follow-up scans.
Aims
The automatic assessment of malignancy probability solely based on nodule appearance and temporal evolution.
Collaborators
Bram van Ginneken, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Colin Jacobs, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Arnaud Arindra Adioso Setio, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Kaman Chung, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Related Publications
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Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.
Venkadesh KV, Setio AAA, Schreuder A, Scholten ET, Chung K, W Wille MM, Saghir Z, van Ginneken B, Prokop M, Jacobs C
Radiology. 2021 May 18; Pages 204433 PUBMED