Guidance-base Diffusion Models for Improving Photoacoustic Image Quality

TL;DR

This paper introduces a guidance-based diffusion model approach to enhance photoacoustic image quality, reducing the need for multiple images and lowering imaging costs by leveraging sensor and imaging condition information.

Contribution

The study proposes a novel guidance method for diffusion models that incorporates sensor and imaging condition data to improve photoacoustic image quality.

Findings

Enhanced image quality with fewer averaged images

Reduced imaging costs in photoacoustic imaging

Effective use of sensor information in diffusion process

Abstract

Photoacoustic(PA) imaging is a non-destructive and non-invasive technology for visualizing minute blood vessel structures in the body using ultrasonic sensors. In PA imaging, the image quality of a single-shot image is poor, and it is necessary to improve the image quality by averaging many single-shot images. Therefore, imaging the entire subject requires high imaging costs. In our study, we propose a method to improve the quality of PA images using diffusion models. In our method, we improve the reverse diffusion process using sensor information of PA imaging and introduce a guidance method using imaging condition information to generate high-quality images.