View source for Projects:MultiscaleShapeSegmentation

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== Objective ==
To represent multiscale variations in a shape population in order to drive the segmentation of deep brain structures, such as the caudate nucleus or the hippocampus.

== Overview ==

=== Shape Representation and Prior ===
The overview of our shape representation is given in Figure 1. Our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population (Figure 2). We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations (Figure 4) [1].

[[Image:Gatech_SW_representation.png|thumb|200px|Figure 1: Steps of the Shape Representation using Spherical Wavelets]]
[[Image:Gatech_SW_mscale_shape.png|thumb|200px|Figure 2: A shape is represented using spherical wavelet coefficients]]

=== Segmentation ===
Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner.

=== Results ===
We applied our algorithm to the caudate nucleus, a brain structure of interest in the study of schizophrenia [2]. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model (ASM) algorithm, by capturing finer shape details.

== References ==
*  [1] Nain D, Haker S, Bobick A, Tannenbaum A. Multiscale 3D Shape Analysis using Spherical Wavelets. Proc MICCAI, Oct 26-29 2005; p 459-467 [1] 
* [2] Nain D, Haker S, Bobick A, Tannenbaum A. Shape-driven 3D Segmentation using Spherical Wavelets. Proc MICCAI, Oct 2-5, 2006. PDF of paper 

== Key Investigators ==
* Core 1:
** Georgia Tech: Delphine Nain, Aaron Bobick, Allen Tannenbaum
** Harvard SPL: Steven Haker

== Collaborators ==

*  Core 1: Martin Styner (UNC)
* Core 2: Jim Miller (GE), Luis Ibanez (Kitware)
* Core 3: James Levitt, Marc Niethammer, Sylvain Bouix, Martha Shenton (Harvard PNL) 

== Links: ==
*  Paper presented in  [[MICCAI_2006|MICCAI 2006, Copenhagen, October 2 - 4, 2006 ]]
* Code: [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]] 
* [[Algorithm:GATech|Georgia Tech Summary Page]]
* [[NA-MIC_Collaborations|NA-MIC_Collaborations]]