Difference between revisions of "2016 Winter Project Week/Projects/ShapeAnalysis"

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==Key Investigators==
 
==Key Investigators==
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Miaomiao Zhang, CSAIL, MIT
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Polina Golland, CSAIL, MIT
 
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Revision as of 17:52, 4 January 2016

Home < 2016 Winter Project Week < Projects < ShapeAnalysis

Key Investigators

Miaomiao Zhang, CSAIL, MIT Polina Golland, CSAIL, MIT

Project Description

Statistical shape analysis develops methods for the geometric study of objects. The means to represent shapes for a group of images is the geometric transformation between each individual and the mean image. One challenge of shape variability quantification is 'the curse of dimensionality', for instance, the transformation grid 128x128x128 as a shape descriptor for a 3D brain image. This makes the inference procedure computationally complicate and time-consuming. An efficient method needs to be developed to handle this complex dataset.

Objective Approach and Plan Progress and Next Steps
  • Develop a low-dimensional statistical shape analysis method on the manifold of diffeomorphic transformations.

Background and References