Comparative Evaluation of Regression Methods for 3D-2D Image Registration
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Machine learning-based improvements to image-based 2D/3D registration were already of interest before the deep learning era.
“Machine learning-based improvements to image-based 2D/3D registration were already of interest before the deep learning era (Gouveia et al., 2012)”
From The Impact of Machine Learning on 2D/3D Registration for Image-Guided Interventions: A Systematic Review and Perspective (2021) · cites this paper as Gouveia et al., 2012
Cited by
Sorted by citations
Unberath, M., Gao, C., Hu, Y., Judish, M., Taylor, R. H., Armand, M., & Grupp, R. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.716007 · Cited by 102 · see citing works
- Authors
- Gouveia, A. I. R., Metz, C., Freire, L., & Klein, S.
- Affiliations
- University of Lisbon (PT)
- Erasmus MC (NL)
- Universidade Politécnica de Lisboa (PT)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 238-245
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1813509888
- Cited by
- 5
- References
- 0
- Citations by year
- 2021: 1 · 2018: 1 · 2015: 1 · 2013: 1 · 2012: 1
- FWCI
- 0.68
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Physics and Astronomy › Radiation › Advanced Radiotherapy Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Keywords
- 2D-3D registration, regression method comparison, coronary CT angiography, digitally reconstructed radiographs, X-ray images, target registration error, radial basis function neural network, support vector regression, multilayer perceptron, polynomial regression, k-nearest neighbors
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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