Publications
2019
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,
A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis. Journal Article
In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019.
Abstract | Links | BibTeX | Tags: biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform
@article{Michoud2019,
title = {A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.},
author = {Michoud L and Huang C and Yatabe M and Bianchi J and et al},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494085/},
doi = {10.1117/12.2506032},
year = {2019},
date = {2019-05-15},
journal = {Proc SPIE-the Int Soc Opt Eng},
volume = {10953},
abstract = {This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.},
keywords = {biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform},
pubstate = {published},
tppubtype = {article}
}
This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,
A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis. Journal Article
In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019.
@article{Michoud2019,
title = {A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.},
author = {Michoud L and Huang C and Yatabe M and Bianchi J and et al},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494085/},
doi = {10.1117/12.2506032},
year = {2019},
date = {2019-05-15},
journal = {Proc SPIE-the Int Soc Opt Eng},
volume = {10953},
abstract = {This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.
2019 |
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,: A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.. In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019. (Type: Journal Article | Abstract | Links | BibTeX | Tags: biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform)@article{Michoud2019, This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts. |