Towards real‐time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images

This study demonstrates how a two-stage network facilitates CBCT-based sCT generation across the entire spine without prior CT knowledge, improving HU accuracy and potentially enabling highly-conformal palliative treatment planning for spinal metastases in real time.

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Publication Details

Journal
Medical Physics
Published
2025-04-21
DOI
https://doi.org/10.1002/mp.17838
Primary Topic
Advanced Radiotherapy Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Towards real‐time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images

David J. Granville, Mehan Haidari, Elsayed Ali
Medical Physics
Advanced Radiotherapy Techniques
article

Towards real‐time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images

David J. Granville, Mehan Haidari, Elsayed Ali
article en

Abstract

This study demonstrates how a two-stage network facilitates CBCT-based sCT generation across the entire spine without prior CT knowledge, improving HU accuracy and potentially enabling highly-conformal palliative treatment planning for spinal metastases in real time.

Medical PhysicsVol. 52(6)
Ottawa Hospital (CA), Nova Scotia Health Authority (CA), Carleton University (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 90%
Advanced Radiotherapy Techniques
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