A denoising diffusion fluid flow generative model for stenotic pipe flows

Aryan Ghazipour; Amirkhosro Kazemi; Amir A. Amini

doi:10.1117/12.3009713

2 April 2024 A denoising diffusion fluid flow generative model for stenotic pipe flows

Aryan Ghazipour, Amirkhosro Kazemi, Amir A. Amini

Author Affiliations +

Proceedings Volume 12930, Medical Imaging 2024: Clinical and Biomedical Imaging; 1293009 (2024) https://doi.org/10.1117/12.3009713
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

Generative models have been used to combat medical image scarcity by generating new samples to increase the size of the training data. The hypothesis of this paper is that Denoising Diffusion Probabilistic Models (DDPM), have the ability to synthesize high quality flow images and potentially obviate the need to rely on time-consuming CFD simulations. As a first step, in this paper, we concentrate on data generation at only the peak flow rate of the simulation and propose a DDPM that, with high accuracy, can generate velocity fields for many unseen flow rates in a fixed in-vitro phantom geometry with rigid walls modeling a vascular stenosis.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Aryan Ghazipour, Amirkhosro Kazemi, and Amir A. Amini "A denoising diffusion fluid flow generative model for stenotic pipe flows", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 1293009 (2 April 2024); https://doi.org/10.1117/12.3009713

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE