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CycleGAN-based image-to-image translation for synthetic contrast enhancement in non-contrast cardiac CT: a ViT-CNN hybrid deep learning approach

Published Online: 2026-04-16

Authors

Park, Doyoung

Kim, Jinsoo

Ruan, Xucong

Chow, Weien

Baskaran, Lohendran
Funding

Funding for this research was provided by:

National Medical Research Council (NMRC/CG2/001a/2021NHCS, CG21APR1006, TA21nov-0001)

SingHealth-Duke-NUS ACP Philanthropy grant (HRDUK230600)

SingHealth-Duke-NUS ACP NCRS grant (07/FY2021/P2/12-A93)
License Information

Text and Data Mining valid from 2026-04-16

Version of Record valid from 2026-05-26
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Article History

Received: 2 December 2025

Accepted: 16 March 2026

First Online: 16 April 2026

Declarations

:

: The study was approved by the Central Institutional Review Board of SingHealth, Singapore (IRB 2022–2521). The study was conducted in accordance with the Declaration of Helsinki. Due to the retrospective nature of the study, the Central Institutional Review Board of SingHealth waived the need to obtain informed consent.

: Not applicable.

: The authors declare no competing interests.

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