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Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture

Crossref DOI link: https://doi.org/10.1007/s11548-025-03323-2

Published Online: 2025-01-20

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Liu, Yi-Kuan

Cisneros, Jorge

Nair, Girish

Stevens, Craig

Castillo, Richard

Vinogradskiy, Yevgeniy

Castillo, Edward https://orcid.org/0000-0003-0523-487X
Funding

Funding for this research was provided by:

NIH National Cancer Institute (R01CA236857, R01CA236857, R01CA236857, R01CA236857)
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Text and Data Mining valid from 2025-01-20

Version of Record valid from 2025-01-20
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Article History

Received: 1 July 2024

Accepted: 7 January 2025

First Online: 20 January 2025

Declarations

:

: EC is a named inventor on granted patent #10932744 related to the CT-perfusions methods. EC also serves as a paid consultant to 4D Medical R&D, Inc., which develops respiratory imaging technologies for clinical and research use. None of the other authors report any potential conflicts of interest with the materials presented.

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