Population studies of neurodegenerative disease and neurodevelopment are supported by ongoing development of feature-specific and sensitive methods that help detect statistical deviations of the anatomical features from the normal brain. A number of MINC tools for morphometric analysis of the brain have been developed, including:

These tools are all part of the MINC tools and can be used individually. They are also implemented in the CIVET pipeline.

Key Publications:

Segmentation

Tohka J, Zijdenbos A, Evans A. Fast and robust parameter estimation for statistical partial volume models in brain MRI. Neuroimage. 2004 Sep;23(1):84-97.
Cocosco CA, Zijdenbos AP, Evans AC. A fully automatic and robust brain MRI tissue classification method. Med Image Anal. 2003 Dec;7(4):513-27.
Dumoulin SO, Hoge RD, Baker CL Jr, Hess RF, Achtman RL, Evans AC. Automatic volumetric segmentation of human visual retinotopic cortex. Neuroimage. 2003 Mar;18(3):576-87.

Automatic sulcal segmentation

Surface Features

Chung MK, Worsley KJ, Robbins S, Paus T, Taylor J, Giedd JN, Rapoport JL, Evans AC. Deformation-based surface morphometry applied to gray matter deformation. Neuroimage. 2003 Feb;18(2):198-213.
Kim JS, Singh V, Lee JK, Lerch J, Ad-Dab’bagh Y, MacDonald D, Lee JM, Kim SI, Evans AC. Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage. 2005 Aug 1;27(1):210-21.
Boucher M, Whitesides S, Evans A. Depth potential function for folding pattern representation, registration and analysis. Med Image Anal. 2009 Apr;13(2):203-14.
Lyttelton O, Boucher M, Robbins S, Evans A. An unbiased iterative group registration template for cortical surface analysis. Neuroimage. 2007 Feb 15;34(4):1535-44.
Chung MK, Worsley KJ, Robbins S, Paus T, Taylor J, Giedd JN, Rapoport JL, Evans AC. Deformation-based surface morphometry applied to gray matter deformation. Neuroimage. 2003 Feb;18(2):198-213.

Deforming polyhedra to match the cortical surface