Projects:longitudinaldwi - Revision history

Anuja at 12:02, 19 August 2012

2012-08-19T12:02:23Z

2012-08-19T12:01:13Z

Application to longitudinal DTI in Huntington Disease

2011-04-12T03:28:57Z

Longitudinal Analysis of DWI image data

2011-04-11T15:59:09Z

Statistical Growth Modeling of Longitudinal DT-MRI

2011-04-11T15:58:06Z

Description

2011-04-11T15:52:58Z

Constrained Data Decomposition and Regression for Longitudinal Fiber Tract Diffusion

2011-04-11T15:52:36Z

Description

2011-04-11T15:50:30Z

Statistical Growth Modeling of Longitudinal DT-MRI

2011-04-11T15:48:44Z

Statistical Growth Modeling of Longitudinal DT-MRI

2011-04-11T15:37:18Z

Statistical Growth Modeling of Longitudinal DT-MRI

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+''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.''
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 == Application to longitudinal DTI in Huntington Disease ==
-to come soon
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 ==Key Investigators==

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	= Longitudinal Analysis of DWI image data =		= Longitudinal Analysis of DWI image data =

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-== Statistical Growth Modeling of Longitudinal DT-MRI ==
+== Growth Modeling of Longitudinal DT-MRI ==
 This research presents a framework to model growth trajectories and to determine significant regional differences in growth pattern characteristics, applied to longitudinal neuroimaging data. We use nonlinear mixed effect modeling where temporal change is modeled by the Gompertz function. The Gompertz function uses intuitive parameters related to delay, rate of change, and expected asymptotic value; all descriptive measures which can answer clinical questions related to growth. Our proposed framework combines nonlinear modeling of individual trajectories, population analysis, and testing for regional differences. We will apply this framework to longitudinal DTI studies of NA-MIC DBP partners, which include acute/follow-up DTI in TBI and serial DTI in the Huntington Diseases PREDICT project, where thee time-points will be available.
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 == Application to longitudinal DTI in Huntington Disease ==

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 ''Sylvain Gouttard, Marcel Prastawa, Elizabeth Bullitt, Casey Goodlett and Guido Gerig, Constrained Data Decomposition and Regression for Analyzing Healthy Aging from Fiber Tract Diffusion Properties, Springer LNCS 5761, Proc. MICCAI’09, pp. 321-328, 2009''
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 == Statistical Growth Modeling of Longitudinal DT-MRI ==
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 ''N. Sadeghi, M. Prastawa, J. H. Gilmore, W. Lin, and G. Gerig, "Spatio-Temporal Analysis of Early Brain Development," in Proceedings IEEE Asilomar Conference on Signals, Systems & Computers, Nov. 2010, in print''
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 == Application to longitudinal DTI in Huntington Disease ==
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 ==Key Investigators==

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	''Sylvain Gouttard, Marcel Prastawa, Elizabeth Bullitt, Casey Goodlett and Guido Gerig, Constrained Data Decomposition and Regression for Analyzing Healthy Aging from Fiber Tract Diffusion Properties, Springer LNCS 5761, Proc. MICCAI’09, pp. 321-328, 2009''		''Sylvain Gouttard, Marcel Prastawa, Elizabeth Bullitt, Casey Goodlett and Guido Gerig, Constrained Data Decomposition and Regression for Analyzing Healthy Aging from Fiber Tract Diffusion Properties, Springer LNCS 5761, Proc. MICCAI’09, pp. 321-328, 2009''
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← Older revision		Revision as of 15:52, 11 April 2011
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	The availability of longitudinal or serial 3D image data for each subject, the image processing gets new opportunities for spatio-temporal processing of 4D datasets. The conventional cross-sectional comparison between subjects are groups at various time points is replaced by comparison and analysis of subject-specific change trajectories. In this project, we focus on the development of longitudinal analysis of DTI.		The availability of longitudinal or serial 3D image data for each subject, the image processing gets new opportunities for spatio-temporal processing of 4D datasets. The conventional cross-sectional comparison between subjects are groups at various time points is replaced by comparison and analysis of subject-specific change trajectories. In this project, we focus on the development of longitudinal analysis of DTI.
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 {| border="0" style="background:transparent;"
-|[[Image:Gompertz.PNG|thumb|250px|Effects to vary the three parameters asymptote, delay, and rate of change of Gompertz growth function.]]
+|[[Image:Gompertz.PNG|thumb|250px|Effects on varying the three parameters asymptote, delay, and rate of change of Gompertz growth function.]]
 |[[Image:Gompertz-FCT.PNG|thumb|250px|Gompertz Growth Function.]]
 |[[Image:ALIC-PLIC.PNG|thumb|250px|Example: Growth of axial and transversal diffusivity (AD, RD) from birth to 2 years of the anterior and posterior left internal capsule (ALIC, PLIC) in early infant study.]]