Accurate malignant risk estimation of pulmonary nodules using deep learning

Principal Investigator

Name
Colin Jacobs

Degrees
Ph.D.

Institution
Radboud University Medical Center

Position Title
Assistant Professor

Email
colinjacobs86@gmail.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-846

Initial CDAS Request Approval
Oct 19, 2021

Title
Accurate malignant risk estimation of pulmonary nodules using deep learning

Summary
In this project, we aim to develop and validate artificial intelligence algorithms that are able to automatically assess the malignancy risk of pulmonary nodules in one or multiple CT scans.
NLST data will be used to train the AI model by extracting information from baseline and follow-up scans.

Aims

To develop and validate a deep learning (DL) algorithms for malignancy risk estimation of pulmonary nodules detected at screening CT.

Collaborators

Kiran Vaidhya Venkadesh, Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
Bram van Ginneken, Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
Mathias Prokop, Department of Medical Imaging, Radboud University Medical Center Nijmegen, Netherlands

Related Publications

• Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules.
  Venkadesh KV, Aleef TA, Scholten ET, Saghir Z, Silva M, Sverzellati N, Pastorino U, van Ginneken B, Prokop M, Jacobs C
  Radiology. 2023 Aug; Volume 308 (Issue 2): Pages e223308 PUBMED