Pseudo-contrast cardiac CT angiography derived from non-contrast CT using conditional generative adversarial networks

Aditya Killekar; Jacek Kwiecinski; Mariusz Kruk; Cezary Kepka; Aakash Shanbhag; Damini Dey; Piotr Slomka

doi:10.1117/12.2654592

3 April 2023 Pseudo-contrast cardiac CT angiography derived from non-contrast CT using conditional generative adversarial networks

Aditya Killekar, Jacek Kwiecinski, Mariusz Kruk, Cezary Kepka, Aakash Shanbhag, Damini Dey, Piotr Slomka

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Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124643F (2023) https://doi.org/10.1117/12.2654592
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Contrast computed tomography angiography (CTA) is utilized in wide variety of applications ranging from clinical practices to emerging technologies. However, radiation exposure, the necessity of contrast administration, as well as the overall complexity of the acquisition are major limitations. We aimed to generate pseudo-contrast CTA, utilizing a conditional generative adversarial network (cGAN). We synthesize realistic contrast CTA from a perfectly registered non-contrast thin slice computed tomography (NCCT). Our method may substitute contrast CTA with a pseudo-contrast CTA for certain clinical applications such as the assessments of cardiac anatomy.

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Aditya Killekar, Jacek Kwiecinski, Mariusz Kruk, Cezary Kepka, Aakash Shanbhag, Damini Dey, and Piotr Slomka "Pseudo-contrast cardiac CT angiography derived from non-contrast CT using conditional generative adversarial networks", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124643F (3 April 2023); https://doi.org/10.1117/12.2654592

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