Algorithm:MGH:New

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Overview of MGH Algorithms

A brief overview of the MGH's algorithms goes here. This should not be much longer than a paragraph. Remember that people visiting your site want to be able to understand very quickly what you're all about and then they want to jump into your site's projects. The projects below are organized into a two column table: the left column is for representative images and the right column is for project overviews. The number of rows corresponds to the number of projects at your site. Put the most interesting and relevant projects at the top of the table. You do not need to organize the table according to subject matter (i.e. do not group all segmentation projects together and all DWI projects together).

MGH Projects

File:Placeholder.png	QDEC: An easy to use GUI for group morphometry studies Difficulty: Medium Impact: High Use cases: See Qdec project page Use case: 'Compare the primary eigendirection in two groups to see if they are the same' Difficulty: Low Impact: Medium See: Qdec user page
File:Placeholder.png	Optimal path calculator (Poistats) Use case: 'Specify 2 points in a diffusion image and tell how connected they are.' Difficulty: High Impact: High
File:Placeholder.png	Engineering:Project:Non-rigid_EPI_registration My objective is to evaluate the benefit of using ITK nonlinear registration for group FA comparisons. More...
File:Placeholder.png	Adding NRRD I/O to Freesurfer
File:Placeholder.png	Spherical Wavelets Cortical Surface Shape Analysis Based on Spherical Wavelets
File:Placeholder.png	Topology Correction Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops
File:Placeholder.png	QBall Visualization
File:Placeholder.png	Tensor-based group comparison (Cramer test) Our objective is to boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests. More...
File:Placeholder.png	Numerical Recipies Replacement Our obejective is to replace algorithms using proprietary numerical recipes in FreeSurfer in efforts to open source FreeSurfer. More...
File:Placeholder.png	Atlas Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms Atlas-based approaches have demonstrated the ability to automatically identify detailed brain structures from 3-D magnetic resonance (MR) brain images. Unfortunately, the accuracy of this type of method often degrades when processing data acquired on a different scanner platform or pulse sequence than the data used for the atlas training. In this paper, we improve the performance of an atlas-based whole brain segmentation method by introducing an intensity renormalization procedure that automatically adjusts the prior atlas intensity model to new input data. Validation using manually labeled test datasets has shown that the new procedure improves the segmentation accuracy (as measured by the Dice coefficient) by 10% or more for several structures including hippocampus, amygdala, caudate, and pallidum. The results verify that this new procedure reduces the sensitivity of the whole brain segmentation method to changes in scanner platforms and improves its accuracy and robustness, which can thus facilitate multicenter or multisite neuroanatomical imaging studies. More...