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Machine Learning with Low Dose CT Data

Principal Investigator
Name
Bennett Landman
Degrees
PhD
Institution
Vanderbilt University
Position Title
Professor
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-993
Initial CDAS Request Approval
Dec 8, 2022
Title
Machine Learning with Low Dose CT Data
Summary
We seek to develop method to integrate assessment of body habitus with lung cancer risk. We are developing both cross-sectional and longitudinal learning frameworks. We are targeting quantitative anatomical modeling (e.g., semantic segmentation), lung nodule identification / classification, and risk stratification. We are developing supporting image processing techniques to harmonize imaging and improve inter-site reproducibility.
Aims

* Segment anatomy within the chest CT field of view
* Identify potentially cancerous lung nodules
* Assess likelihood of cancer within specific nodules and a time point in a holistic manner.
* Perform image processing to improve inter-site consistency and enhance performance of the above objectives.

Collaborators

Fabien Maldonado, VUMC
Kim Lori Sandler, VUMC
Tom Lasko, VUMC

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