Optimization-Based Calibration for Intravascular Ultrasound Volume Reconstruction
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866912557739016192 |
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| author | Beaudet, Karl-Philippe Hadramy, Sidaty El Cattin, Philippe C Verde, Juan Cotin, Stéphane |
| author_facet | Beaudet, Karl-Philippe Hadramy, Sidaty El Cattin, Philippe C Verde, Juan Cotin, Stéphane |
| contents | Intraoperative ultrasound images are inherently challenging to interpret in liver surgery due to the limited field of view and complex anatomical structures. Bridging the gap between preoperative and intraoperative data is crucial for effective surgical guidance. 3D IntraVascular UltraSound (IVUS) offers a potential solution by enabling the reconstruction of the entire organ, which facilitates registration between preoperative computed tomography (CT) scans and intraoperative IVUS images. In this work, we propose an optimization-based calibration method using a 3D-printed phantom for accurate 3D Intravascular Ultrasound volume reconstruction. Our approach ensures precise alignment of tracked IVUS data with preoperative CT images, improving intraoperative navigation. We validated our method using in vivo swine liver images, achieving a calibration error from 0.88 to 1.80 mm and a registration error from 3.40 to 5.71 mm between the 3D IVUS data and the corresponding CT scan. Our method provides a reliable and accurate means of calibration and volume reconstruction. It can be used to register intraoperative ultrasound images with preoperative CT images in the context of liver surgery, and enhance intraoperative guidance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_20605 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimization-Based Calibration for Intravascular Ultrasound Volume Reconstruction Beaudet, Karl-Philippe Hadramy, Sidaty El Cattin, Philippe C Verde, Juan Cotin, Stéphane Computer Vision and Pattern Recognition Intraoperative ultrasound images are inherently challenging to interpret in liver surgery due to the limited field of view and complex anatomical structures. Bridging the gap between preoperative and intraoperative data is crucial for effective surgical guidance. 3D IntraVascular UltraSound (IVUS) offers a potential solution by enabling the reconstruction of the entire organ, which facilitates registration between preoperative computed tomography (CT) scans and intraoperative IVUS images. In this work, we propose an optimization-based calibration method using a 3D-printed phantom for accurate 3D Intravascular Ultrasound volume reconstruction. Our approach ensures precise alignment of tracked IVUS data with preoperative CT images, improving intraoperative navigation. We validated our method using in vivo swine liver images, achieving a calibration error from 0.88 to 1.80 mm and a registration error from 3.40 to 5.71 mm between the 3D IVUS data and the corresponding CT scan. Our method provides a reliable and accurate means of calibration and volume reconstruction. It can be used to register intraoperative ultrasound images with preoperative CT images in the context of liver surgery, and enhance intraoperative guidance. |
| title | Optimization-Based Calibration for Intravascular Ultrasound Volume Reconstruction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2508.20605 |