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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2307.14288 |
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| _version_ | 1866929263559573504 |
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| author | Paccini, Martina Paschina, Giacomo De Beni, Stefano Stefanov, Andrei Kolev, Velizar Patanè, Giuseppe |
| author_facet | Paccini, Martina Paschina, Giacomo De Beni, Stefano Stefanov, Andrei Kolev, Velizar Patanè, Giuseppe |
| contents | This paper presents an innovative automatic fusion imaging system that combines 3D CT/MR images with real-time ultrasound (US) acquisition. The system eliminates the need for external physical markers and complex training, making image fusion feasible for physicians with different experience levels. The integrated system involves a portable 3D camera for patient-specific surface acquisition, an electromagnetic tracking system, and US components. The fusion algorithm comprises two main parts: skin segmentation and rigid co-registration, both integrated into the US machine. The co-registration software aligns the surface extracted from CT/MR images with patient-specific coordinates, facilitating rapid and effective fusion. Experimental testing in different settings validates the system's accuracy, computational efficiency, noise robustness, and operator independence. The co-registration error remains under the acceptable range of~$1$ cm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_14288 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | US \& MRI Image Fusion Based on Markerless Skin Registration Paccini, Martina Paschina, Giacomo De Beni, Stefano Stefanov, Andrei Kolev, Velizar Patanè, Giuseppe Computer Vision and Pattern Recognition This paper presents an innovative automatic fusion imaging system that combines 3D CT/MR images with real-time ultrasound (US) acquisition. The system eliminates the need for external physical markers and complex training, making image fusion feasible for physicians with different experience levels. The integrated system involves a portable 3D camera for patient-specific surface acquisition, an electromagnetic tracking system, and US components. The fusion algorithm comprises two main parts: skin segmentation and rigid co-registration, both integrated into the US machine. The co-registration software aligns the surface extracted from CT/MR images with patient-specific coordinates, facilitating rapid and effective fusion. Experimental testing in different settings validates the system's accuracy, computational efficiency, noise robustness, and operator independence. The co-registration error remains under the acceptable range of~$1$ cm. |
| title | US \& MRI Image Fusion Based on Markerless Skin Registration |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2307.14288 |