The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Three-dimensional modeling for functional analysis of cardiac images, a review
Abstract
Three-dimensional (3-D) imaging of the heart is a rapidly developing area of research in medical imaging. Advances in hardware and methods for fast spatio-temporal cardiac imaging are extending the frontiers of clinical diagnosis and research on cardiovascular diseases. In the last few years, many approaches have been proposed to analyze images and extract parameters of cardiac shape and function from a variety of cardiac imaging modalities. In particular, techniques based on spatio-temporal geometric models have received considerable attention. This paper surveys the literature of two decades of research on cardiac modeling. The contribution of the paper is three-fold: 1) to serve as a tutorial of the field for both clinicians and technologists, 2) to provide an extensive account of modeling techniques in a comprehensive and systematic manner, and 3) to critically review these approaches in terms of their performance and degree of clinical evaluation with respect to the final goal of cardiac functional analysis. From this review it is concluded that whereas 3-D model-based approaches have the capability to improve the diagnostic value of cardiac images, issues as robustness, 3-D interaction, computational complexity and clinical validation still require significant attention.
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Cites
A method for registration of 3-D shapes
Besl, P. J., & McKay, N. D. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.121791 · Cited by 18,103
Kass, M., Witkin, A., & Terzopoulos, D. (1988) · International Journal of Computer Vision · doi:10.1007/bf00133570 · Cited by 17,070
Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
Osher, S., & Sethian, J. A. (1988) · Journal of Computational Physics · doi:10.1016/0021-9991(88)90002-2 · Cited by 14,062
Hopfield, J. J. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.10.3088 · Cited by 6,918
Differential geometry of curves and surfaces
(2011) · Choice Reviews Online · doi:10.5860/choice.48-3330 · Cited by 3,706
Shape modeling with front propagation: a level set approach
Malladi, R., Sethian, J. A., & Vemuri, B. C. (1995) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.368173 · Cited by 3,158
Surface reconstruction from unorganized points
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., & Stuetzle, W. (1992) · Proceedings of the 19th annual conference on Computer graphics and interactive techniques · doi:10.1145/133994.134011 · Cited by 2,730
Free-form deformation of solid geometric models
Sederberg, T. W., & Parry, S. R. (1986) · ACM SIGGRAPH Computer Graphics · doi:10.1145/15886.15903 · Cited by 2,577
On active contour models and balloons
Cohen, L. D. (1991) · CVGIP: Image Understanding · doi:10.1016/1049-9660(91)90028-n · Cited by 2,153
Deformable models in medical image analysis: a survey
McInerney, T., & Terzopoulos, D. (1996) · Medical Image Analysis · doi:10.1016/s1361-8415(96)80007-7 · Cited by 1,913
Cited by
Deformable medical image registration: a survey
Sotiras, A., Davatzikos, C., & Paragios, N. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2265603 · Cited by 1,587
“cardiac and respiratory motion) the key element in diagnosis becomes their spatio-temporal behavior [1, 2].”
BackgroundUltrasound image segmentation: a survey
Noble, J. A., & Boukerroui, D. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.877092 · Cited by 1,157
Three-dimensional cardiac computational modelling: methods, features and applications.
Lopez-Perez, A., Sebastian, R., & Ferrero, J. M. (2015) · BioMedical Engineering OnLine · doi:10.1186/s12938-015-0033-5 · Cited by 151
Automatic segmentation of the right ventricle from cardiac MRI using a learning‐based approach
Avendi, M. R., Kheradvar, A., & Jafarkhani, H. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26631 · Cited by 135
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge
Suinesiaputra, A., Dhooge, J., Duchateau, N., Ehrhardt, J., Frangi, A. F., Gooya, A., Grau, V., Lekadir, K., Lu, A., Mukhopadhyay, A., et al. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2652449 · Cited by 95
Self-citation
Metadata
- Authors
- Frangi, A. F., Niessen, W. J., & Viergever, M. A.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2001
- Volume
- 20
- Issue
- 1
- Pages
- 2-5
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2171790646
- Cited by
- 533
- References
- 82
- FWCI
- 21.88
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
