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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.06354 |
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| _version_ | 1866910820209786880 |
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| author | Eguchi, Tatsuhiro Takezaki, Shumpei Shimano, Mihoko Yagi, Takayuki Bise, Ryoma |
| author_facet | Eguchi, Tatsuhiro Takezaki, Shumpei Shimano, Mihoko Yagi, Takayuki Bise, Ryoma |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_06354 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Guidance-base Diffusion Models for Improving Photoacoustic Image Quality Eguchi, Tatsuhiro Takezaki, Shumpei Shimano, Mihoko Yagi, Takayuki Bise, Ryoma Computer Vision and Pattern Recognition 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. |
| title | Guidance-base Diffusion Models for Improving Photoacoustic Image Quality |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2502.06354 |