A Novel Framework for Integrating 3D Ultrasound into Percutaneous Liver Tumour Ablation
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915359990218752 |
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| author | Xing, Shuwei Cool, Derek W. Tessier, David Chen, Elvis C. S. Peters, Terry M. Fenster, Aaron |
| author_facet | Xing, Shuwei Cool, Derek W. Tessier, David Chen, Elvis C. S. Peters, Terry M. Fenster, Aaron |
| contents | 3D ultrasound (US) imaging has shown significant benefits in enhancing the outcomes of percutaneous liver tumour ablation. Its clinical integration is crucial for transitioning 3D US into the therapeutic domain. However, challenges of tumour identification in US images continue to hinder its broader adoption. In this work, we propose a novel framework for integrating 3D US into the standard ablation workflow. We present a key component, a clinically viable 2D US-CT/MRI registration approach, leveraging 3D US as an intermediary to reduce registration complexity. To facilitate efficient verification of the registration workflow, we also propose an intuitive multimodal image visualization technique. In our study, 2D US-CT/MRI registration achieved a landmark distance error of approximately 2-4 mm with a runtime of 0.22s per image pair. Additionally, non-rigid registration reduced the mean alignment error by approximately 40% compared to rigid registration. Results demonstrated the efficacy of the proposed 2D US-CT/MRI registration workflow. Our integration framework advanced the capabilities of 3D US imaging in improving percutaneous tumour ablation, demonstrating the potential to expand the therapeutic role of 3D US in clinical interventions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_21162 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Novel Framework for Integrating 3D Ultrasound into Percutaneous Liver Tumour Ablation Xing, Shuwei Cool, Derek W. Tessier, David Chen, Elvis C. S. Peters, Terry M. Fenster, Aaron Image and Video Processing Artificial Intelligence 3D ultrasound (US) imaging has shown significant benefits in enhancing the outcomes of percutaneous liver tumour ablation. Its clinical integration is crucial for transitioning 3D US into the therapeutic domain. However, challenges of tumour identification in US images continue to hinder its broader adoption. In this work, we propose a novel framework for integrating 3D US into the standard ablation workflow. We present a key component, a clinically viable 2D US-CT/MRI registration approach, leveraging 3D US as an intermediary to reduce registration complexity. To facilitate efficient verification of the registration workflow, we also propose an intuitive multimodal image visualization technique. In our study, 2D US-CT/MRI registration achieved a landmark distance error of approximately 2-4 mm with a runtime of 0.22s per image pair. Additionally, non-rigid registration reduced the mean alignment error by approximately 40% compared to rigid registration. Results demonstrated the efficacy of the proposed 2D US-CT/MRI registration workflow. Our integration framework advanced the capabilities of 3D US imaging in improving percutaneous tumour ablation, demonstrating the potential to expand the therapeutic role of 3D US in clinical interventions. |
| title | A Novel Framework for Integrating 3D Ultrasound into Percutaneous Liver Tumour Ablation |
| topic | Image and Video Processing Artificial Intelligence |
| url | https://arxiv.org/abs/2506.21162 |