Algorithm:Utah2 - Revision history

Anuja: /* Tract-based longitudinal modeling of DTI data */

2014-10-15T23:19:47Z

Tract-based longitudinal modeling of DTI data

Anuja: /* Tract-based longitudinal modeling of DTI data */

2014-10-15T23:18:52Z

Tract-based longitudinal modeling of DTI data

Jfishbaugh: /* Utah 2 Projects */

2014-10-14T05:39:11Z

Utah 2 Projects

Jfishbaugh: /* Utah 2 Projects */

2014-10-14T05:38:35Z

Utah 2 Projects

Jfishbaugh: /* Utah 2 Projects */

2014-10-14T05:38:10Z

Utah 2 Projects

Jfishbaugh at 05:36, 14 October 2014

2014-10-14T05:36:42Z

Jfishbaugh at 05:36, 14 October 2014

2014-10-14T05:36:23Z

Jfishbaugh: /* Utah 2 Projects */

2014-10-14T05:35:36Z

Utah 2 Projects

Jfishbaugh: /* Analysis of Longitudinal Shape Variability */

2014-10-14T05:29:56Z

Analysis of Longitudinal Shape Variability

Jfishbaugh: /* Smooth Growth Trajectories from Time Series Shape Data */

2014-10-14T05:24:25Z

Smooth Growth Trajectories from Time Series Shape Data

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 [[Projects:TractLongitudinalDTI|More...]]
-''A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “ Parametric Regression Scheme For Distributions: Analysis of DTI Fiber Tract Diffusion Changes In Early Brain Development,” In Proceedings of the 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp. 559-562. 2014.''
+''A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “ Parametric Regression Scheme For Distributions: Analysis of DTI Fiber Tract Diffusion Changes In Early Brain Development,” In Proceedings of IEEE ISBI 2014, pp. 559-562. 2014.''
-''A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “Spatiotemporal Modeling of Discrete-Time Distribution-Valued Data Applied to DTI Tract Evolution in Infant Neurodevelopment,” In Proceedings of the 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI), pp. 684--687. 2013.''
+''A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “Spatiotemporal Modeling of Discrete-Time Distribution-Valued Data Applied to DTI Tract Evolution in Infant Neurodevelopment,” In Proceedings of IEEE ISBI 2013, pp. 684--687. 2013.''
 ''A. Sharma, S. Durrleman, J.H. Gilmore, G. Gerig. “Longitudinal Growth Modeling of Discrete-Time Functions with Application to DTI Tract Evolution in Early Neurodevelopment,” In Proceedings of IEEE ISBI 2012, pp. 1397--1400. 2012.''

@@ Line 71: / Line 71: @@
 [[Projects:TractLongitudinalDTI|More...]]
-''Sharma, A., Durrleman, S. ,  Gilmore, J.H. ,  Gerig, G. Longitudinal growth modeling of discrete-time functions with application to DTI tract evolution in early neurodevelopment. Proc. of 9th IEEE International Symposium on Biomedical Imaging (ISBI May'12), p.1397-1400.''
+''A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “ Parametric Regression Scheme For Distributions: Analysis of DTI Fiber Tract Diffusion Changes In Early Brain Development,” In Proceedings of the 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp. 559-562. 2014.''
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 [[Projects:DiffeoMixedEffects|More...]]
-''Muralidharan, P., Fishbaugh, J., Johnson, H., Durrleman, S., Paulsen, J., Gerig, G., Fletcher, P.T. Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. Proc. of Medical Image Computing and Computer Assisted Intervention (MICCAI '14). (2014)''
+''Muralidharan, P., Fishbaugh, J., Johnson, H., Durrleman, S., Paulsen, J., Gerig, G., Fletcher, P.T. Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. Proc. of Medical Image Computing and Computer Assisted Intervention (MICCAI '14). (2014).''
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-| style="width:15%" | [[Image:Compare_caudates.png|200px]]
+| style="width:15%" | [[Image:Caudate_shapshot.png|200px]]
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 ''Muralidharan, P., Fishbaugh, J., Johnson, H., Durrleman, S., Paulsen, J., Gerig, G., Fletcher, P.T. Diffeomorphic shape trajectories for improved longitudinal segmentation and statistics. Proc. of Medical Image Computing and Computer Assisted Intervention (MICCAI '14). (2014)''
 | style="width:15%" | [[Image:Geodesic_subcort_panel.png|200px]]
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 <font color="red">'''Ongoing: '''</font> Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations.  In this project, we develop a new methods for the statistical analysis of longitudinal shape variability.
 [[Projects:LongitudinalShapeAnalysis|More...]]
 ''Fishbaugh, J., Prastawa, M., Durrleman, S., Piven, J., Gerig, G. Analysis of Longitudinal Shape Variability via Subject Specific Growth Modeling. In N. Ayache et al. (Eds.): MICCAI 2012, Part I, LNCS 7510, pp. 730--737. (2012)''

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 == [[Projects:LongitudinalShapeAnalysis|Analysis of Longitudinal Shape Variability]] ==
-<font color="red">'''Ongoing: '''</font> Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations.  In this project, we develop a new method for the statistical analysis of longitudinal shape variability.
+<font color="red">'''Ongoing: '''</font> Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations.  In this project, we develop a new methods for the statistical analysis of longitudinal shape variability.
 [[Projects:LongitudinalShapeAnalysis|More...]]

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 == [[Projects:Utah2ShapeRegression|Smooth Growth Trajectories from Time Series Shape Data]] ==
-<font color="red">'''Ongoing (Updated 08/16/12):'''</font>  Clinical research is interested in the spatiotemporal analysis of changes of anatomical shapes and structures, which potentially leads to improved understanding of the rate of change, locality and growth trajectory of structures of interest. This project develops a new methodology for the generation of a continuous growth model generated from a sparse set of shapes.
+<font color="red">'''Ongoing:'''</font>  Clinical research is interested in the spatiotemporal analysis of changes of anatomical shapes and structures, which potentially leads to improved understanding of the rate of change, locality and growth trajectory of structures of interest. This project develops a new methodology for the generation of a continuous growth model generated from a sparse set of shapes.
 [[Projects:Utah2ShapeRegression|More...]]