Guidance-base Diffusion Models for Improving Photoacoustic Image Quality
This work addresses the problem of high imaging costs in photoacoustic imaging for medical professionals and researchers, offering an incremental solution to improve image quality.
The authors tackled the problem of poor image quality in photoacoustic imaging, proposing a method to improve image quality using diffusion models, which can potentially reduce the need for averaging many single-shot images. The result is the generation of high-quality images.
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.