Guidance-base Diffusion Models for Improving Photoacoustic Image Quality


Tatsuhiro Eguchi (Kyushu University, Tokyo Institute of Technology), Shumpei Takezaki (Kyushu University), Mihoko Shimano (National Institute of Informatics), Takayuki Yagi (Tokyo Institute of Technology, Tokyo Institute of Technology), Ryoma Bise (Kyushu University, Faculty of Information Science and Electrical Engineering)
The 35th British Machine Vision Conference
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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.

Citation

@inproceedings{Eguchi_2024_BMVC,
author    = {Tatsuhiro Eguchi and Shumpei Takezaki and Mihoko Shimano and Takayuki Yagi and Ryoma Bise},
title     = {Guidance-base Diffusion Models for Improving Photoacoustic Image Quality},
booktitle = {35th British Machine Vision Conference 2024, {BMVC} 2024, Glasgow, UK, November 25-28, 2024},
publisher = {BMVA},
year      = {2024},
url       = {https://papers.bmvc2024.org/0609.pdf}
}


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