Toward Accurate and Robust 2-D/3-D Registration of Implant Models to Single-Plane Fluoroscopy
Integrity signals
Registry
Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Feature-based 2D/3D registration methods require features or anatomical landmarks that are specific to every object and must be selected with domain knowledge and be clearly visible in target images.
“However, these features and anatomical landmarks are specific to every object and must be selected with domain knowledge and such that they are clearly visible in the target images.”
From A Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers (2024) · cites this paper as [11]
Cited by
Sorted by citations
A CNN Regression Approach for Real-Time 2D/3D Registration
Miao, S., Wang, Z. J., & Liao, R. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2521800 · Cited by 514 · 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
“Such examples include SIFT features for femur [9], Generalized Hough Transform (GHT) for spine vertebrae [10], learning-based shape encodings for metal implants [11], etc.”
Method
- Authors
- Miao, S., Liao, R., Lucas, J., & Chefd’hotel, C.
- Affiliations
- Siemens (United States) (US)
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Pages
- 97-106
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1456877
- Cited by
- 10
- References
- 0
- Citations by year
- 2024: 2 · 2023: 3 · 2021: 1 · 2020: 2 · 2019: 1 · 2016: 1
- FWCI
- 0.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Physical Sciences › Physics and Astronomy › Radiation › Advanced Radiotherapy Techniques
- Keywords
- pose initialization, silhouette matching, shape context, Jensen-Shannon divergence, intensity-based registration, hierarchical optimization, depth estimation, X-ray simulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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