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Statistical Analysis of Anatomy from Medical Images Tom Fletcher School of Computing University of Utah National Alliance for Medical Image Computing.

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Presentation on theme: "Statistical Analysis of Anatomy from Medical Images Tom Fletcher School of Computing University of Utah National Alliance for Medical Image Computing."— Presentation transcript:

1 Statistical Analysis of Anatomy from Medical Images Tom Fletcher School of Computing University of Utah National Alliance for Medical Image Computing

2 What is an Average Brain? ? Simple, linear statistics do not capture anatomical shapeSimple, linear statistics do not capture anatomical shape Average anatomy has minimal deformation to input dataAverage anatomy has minimal deformation to input data Nonlinear statistics of shape are neededNonlinear statistics of shape are needed

3 What is an Average Brain? Intensity Average Shape Average

4 Combining Structural and Diffusion Tensor MRI

5

6

7 Regression of FA Genu of the Corpus Callosum (CC) Raw Data Scatterplot Regression w/ std dev

8 Language Networks in Autism A key diagnostic feature of autism is impairment in communicationA key diagnostic feature of autism is impairment in communication The arcuate fasciculus is a white matter tract crucial in languageThe arcuate fasciculus is a white matter tract crucial in language Is the arcuate fasciculus different in autism?Is the arcuate fasciculus different in autism?

9 Arcuate Fasciculus

10 Arcuate Analysis in Autism

11 How Does the Brain Change in Normal Aging? Infer structure of the brain as a function of age from a population (3D MRI)Infer structure of the brain as a function of age from a population (3D MRI) Regression of brain shapeRegression of brain shape Healthy adult brain image database (Bullitt) ~100 healthy adults ages 20-80Healthy adult brain image database (Bullitt) ~100 healthy adults ages 20-80

12 Regression of Scalar Data

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14 Kernel Regression of Deformable Images Davis, Fletcher, Bullit, Joshi, ICCV 2008: Marr Prize (Best Paper)

15 Regression of Aging Brain

16 4042444648 5052545658

17 Acknowledgements Collaborators:Collaborators: –SCI Institute: Ross Whitaker, Sarang Joshi, Guido Gerig –Utah Autism: Janet Lainhart, Molly Dubray –Aging: Liz Bullitt (UNC) Students:Students: –Ran Tao, Saurav Basu, Won-Ki Jeong, Brad Davis Funding:Funding: –NA-MIC: NIH Grant U54 EB005149 –Autism Speaks Fellowship

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