System and Method for 3-D/3-D Registration between Non-contrast-enhanced CBCT and Contrast-Enhanced CT for Abdominal Aortic Aneurysm Stenting
Open accessAbstract
In this paper, we present an image guidance system for abdominal aortic aneurysm stenting, which brings pre-operative 3-D computed tomography (CT) into the operating room by registering it against intra-operative non-contrast-enhanced cone-beam CT (CBCT). Registration between CT and CBCT volumes is a challenging task due to two factors: the relatively low signal-to-noise ratio of the abdominal aorta in CBCT without contrast enhancement, and the drastically different field of view between the two image modalities. The proposed automatic registration method handles the first issue through a fast quasi-global search utilizing surrogate 2-D images, and solves the second problem by relying on neighboring dominant structures of the abdominal aorta (i.e. the spine) for initial coarse alignment, and using a confined and image-processed volume of interest around the abdominal aorta for fine registration. The proposed method is validated offline using 17 clinical datasets, and achieves 1.48 mm target registration error and 100% success rate in 2.83 s. The prototype system has been installed in hospitals for clinical trial and applied in around 30 clinical cases, with 100% success rate reported qualitatively.
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Registration pose error, TRE, and success rate are general measures to report 2D/3D registration performance, commonly used in the literature.
“Our results presented using registration pose error, TRE, and success rate are general measures to report the 2D/3D registration performance, which are commonly used in the literature [51], [18], [24].”
From A Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers (2024) · cites this paper as [51]
Section 5 (Experiments and Results; page unavailable) uses TRE and success rate to evaluate registration performance. It evaluates 3-D/3-D registration, however, and does not report registration pose error or establish that all three measures are commonly used for 2-D/3-D registration. (LLM, conf=0.87)
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Research works printed but not linked: 8
- Creager, M.A., et al.: Aneurysmal disease of the aorta and its branches. In: Vascular Medicine: A Textbook of Vascular Biology and Disease, pp. 901-925 (1996)
- Pluim, J.P.W., et al.: Mutual-information-based registration of medical images: a survey. TMI 22(8), 986-1004 (2003)
- Thévenaz, P., et al.: Optimization of mutual information for multiresolution image registration. TMI 9(12), 2083-2099 (2000)
- Matsopoulos, G.K., et al.: Automatic retinal image registration scheme using global optimization techniques. TITB 3(1), 47-60 (1999)
- Rouet, J.M., et al.: Genetic algorithms for a robust 3-d mr-ct registration. TITB 4(2), 126-136 (2000)
- Wells, W.M., et al.: Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1(1), 35-51 (1996)
- Lombaert, H., et al.: A multilevel banded graph cuts method for fast image seg- mentation. In: ICCV, vol. 1, pp. 259-265. IEEE (2005)
- Gunnar, F., et al.: Improving deriche-style recursive gaussian filters. JMIV 26(3), 293-299 (2006)
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An artificial agent for robust image registration
Liao, R., Miao, S., De Tournemire, P., Grbic, S., Kamen, A., Mansi, T., & Comaniciu, D. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.11230 · Cited by 199 · see citing works
Self-citationA Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers
Gao, C., Feng, A., Liu, X., Taylor, R. H., Armand, M., & Unberath, M. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3299588 · Cited by 36 · see citing works
“Our results presented using registration pose error, TRE, and success rate are general measures to report the 2D/3D registration performance, which are commonly used in the literature [18], [24], [51].”
Result
- Authors
- Miao, S., Liao, R., Pfister, M., Zhang, L., & Ordy, V.
- Affiliations
- Siemens (United States) (US)
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Volume
- 16
- Issue
- Pt 1
- Pages
- 380-387
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W125199751
- Cited by
- 17
- References
- 0
- Citations by year
- 2023: 1 · 2021: 2 · 2020: 2 · 2019: 3 · 2018: 1 · 2017: 2 · 2016: 3 · 2015: 2 · 2014: 1
- FWCI
- 1.28
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
- Health Sciences › Dentistry › Oral Surgery › Dental Radiography and Imaging
- Keywords
- cone-beam computed tomography, non-contrast-enhanced imaging, contrast-enhanced CT, abdominal aortic aneurysm, image-guided surgery, intraoperative imaging, target registration error, volume of interest
- MeSH terms
- Blood Vessel Prosthesis, Contrast Media, Humans, Pattern Recognition, Automated, Pilot Projects, Radiography, Abdominal, Sensitivity and Specificity, Subtraction Technique, Tomography, X-Ray Computed, Reproducibility of Results, Stents, Aortic Aneurysm, Abdominal, Prosthesis Implantation, Imaging, Three-Dimensional, Surgery, Computer-Assisted
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