Development and validation of an AI-based lung lobe auto-contouring tool using radiation therapy planning free-breathing images
Peter Ciaccio, Joseph Lombardo, Andrew Fuquay, Soroush Pahlavian, Rachel Grimm, Jun Kang, Wookjin Choi, Paul Sullivan, Yevgeniy Vinogradskiy · 2025
Read Development and validation of an AI-based lung lobe auto-contouring tool using radiation therapy planning free-breathing images by Peter Ciaccio, Joseph Lombardo, Andrew Fuquay, Soroush Pahlavian, Rachel Grimm, Jun Kang, Wookjin Choi, Paul Sullivan, Yevgeniy Vinogradskiy (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12768033.txt.
Description
Peter Ciaccio and co-authors build and validate an AI tool that outlines lung lobes on planning scans in a 2025 paper. Radiation dose judged lobe by lobe predicts lung toxicity better, but hand-drawing five lobes is slow and hard. Automation could make lobar dosimetry routine.
A clinician contoured the lobes of fifty patients from two centers on free-breathing scans. A residual 3D network trained on forty cases and was checked against expert outlines on the rest. Accuracy results fill the paper. If auto-contours prove trustworthy, planners gain finer toxicity forecasts without hours of manual tracing per patient.
Catalog record
| CREATOR | Peter Ciaccio, Joseph Lombardo, Andrew Fuquay, Soroush Pahlavian, Rachel Grimm, Jun Kang, Wookjin Choi, Paul Sullivan, Yevgeniy Vinogradskiy |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 15 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |