Diffusion Model for Generating Synthetic Contrast Enhanced CT from Non-Enhanced Heart Axial CT Images

Victor Ferreira, Anselmo Cardoso de Paiva, Aristofanes Correa Silva, João Dallyson Sousa de Almeida, Geraldo Braz Junior, Francesco Renna

2024

Abstract

This work proposes the use of a deep learning-based adversarial diffusion model to address the translation of contrast-enhanced from non-contrast-enhanced computed tomography (CT) images of the heart. The study overcomes challenges in medical image translation by combining concepts from generative adversarial networks (GANs) and diffusion models. Results were evaluated using the Peak signal to noise ratio (PSNR) and structural index similarity (SSIM) to demonstrate the model’s effectiveness in generating contrast images while preserving quality and visual similarity. Despite successes, Root Mean Square Error (RMSE) analysis indicates persistent challenges, highlighting the need for continuous improvements. The intersection of GANs and diffusion models promises future advancements, significantly contributing to clinical practice. The table compares CyTran, CycleGAN, and Pix2Pix networks with the proposed model, indicating directions for improvement.

Paper Citation

in Harvard Style

Ferreira V., Cardoso de Paiva A., Correa Silva A., Dallyson Sousa de Almeida J., Braz Junior G. and Renna F. (2024). Diffusion Model for Generating Synthetic Contrast Enhanced CT from Non-Enhanced Heart Axial CT Images. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 857-864. DOI: 10.5220/0012724600003690

in Bibtex Style

@conference{iceis24,
author={Victor Ferreira and Anselmo Cardoso de Paiva and Aristofanes Correa Silva and João Dallyson Sousa de Almeida and Geraldo Braz Junior and Francesco Renna},
title={Diffusion Model for Generating Synthetic Contrast Enhanced CT from Non-Enhanced Heart Axial CT Images},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={857-864},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012724600003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Diffusion Model for Generating Synthetic Contrast Enhanced CT from Non-Enhanced Heart Axial CT Images
SN - 978-989-758-692-7
AU - Ferreira V.
AU - Cardoso de Paiva A.
AU - Correa Silva A.
AU - Dallyson Sousa de Almeida J.
AU - Braz Junior G.
AU - Renna F.
PY - 2024
SP - 857
EP - 864
DO - 10.5220/0012724600003690
PB - SciTePress