Literature DB >> 11467907

An efficient algorithm for topologically correct segmentation of the cortical sheet in anatomical mr volumes.

N Kriegeskorte1, R Goebel.   

Abstract

Polygon-mesh representations of the cortices of individual subjects are of anatomical interest, aid visualization of functional imaging data and provide important constraints for their statistical analysis. Due to noise and partial volume sampling, however, conventional segmentation methods rarely yield a voxel object whose outer boundary represents the folded cortical sheet without topological errors. These errors, called handles, have particularly deleterious effects when the polygon mesh constructed from the segmented voxel representation is inflated or flattened. So far handles had to be removed by cumbersome manual editing, or the computationally more expensive method of reconstruction by morphing had to be used, incorporating the a priori constraint of simple topology into the polygon-mesh model. Here we describe a linear time complexity algorithm that automatically detects and removes handles in presegmentations of the cortex obtained by conventional methods. The algorithm's modifications reflect the true structure of the cortical sheet. The core component of our method is a region growing process that starts deep inside the object, is prioritized by the distance-to-surface of the voxels considered for inclusion and is selftouching-sensitive, i.e., voxels whose inclusion would add a handle are never included. The result is a binary voxel object identical to the initial object except for "cuts" located in the thinnest part of each handle. By applying the same method to the inverse object, an alternative set of solutions is determined, correcting the errors by addition instead of deletion of voxels. For each handle separately, the solution more consistent with the intensities of the original anatomical MR scan is chosen. The accuracy of the resulting polygon-mesh reconstructions has been validated by visual inspection, by quantitative comparison to an expert's manual corrections, and by crossvalidation between reconstructions from different scans of the same subject's cortex. Copyright 2001 Academic Press.

Mesh:

Year:  2001        PMID: 11467907     DOI: 10.1006/nimg.2001.0831

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  53 in total

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2.  Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest.

Authors:  Vincent G van de Ven; Elia Formisano; David Prvulovic; Christian H Roeder; David E J Linden
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Authors:  Rachel Aine Yotter; Robert Dahnke; Paul M Thompson; Christian Gaser
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Review 4.  Segmentation of human brain using structural MRI.

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Journal:  MAGMA       Date:  2016-01-06       Impact factor: 2.310

Review 5.  Cortical cartography and Caret software.

Authors:  David C Van Essen
Journal:  Neuroimage       Date:  2011-10-28       Impact factor: 6.556

6.  Cortical reconstruction using implicit surface evolution: accuracy and precision analysis.

Authors:  Duygu Tosun; Maryam E Rettmann; Daniel Q Naiman; Susan M Resnick; Michael A Kraut; Jerry L Prince
Journal:  Neuroimage       Date:  2005-11-02       Impact factor: 6.556

Review 7.  Cortical surface segmentation and mapping.

Authors:  Duygu Tosun; Maryam E Rettmann; Xiao Han; Xiaodong Tao; Chenyang Xu; Susan M Resnick; Dzung L Pham; Jerry L Prince
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

8.  Simplified intersubject averaging on the cortical surface using SUMA.

Authors:  Brenna D Argall; Ziad S Saad; Michael S Beauchamp
Journal:  Hum Brain Mapp       Date:  2006-01       Impact factor: 5.038

9.  Analysis of functional image analysis contest (FIAC) data with brainvoyager QX: From single-subject to cortically aligned group general linear model analysis and self-organizing group independent component analysis.

Authors:  Rainer Goebel; Fabrizio Esposito; Elia Formisano
Journal:  Hum Brain Mapp       Date:  2006-05       Impact factor: 5.038

10.  Topology correction of segmented medical images using a fast marching algorithm.

Authors:  Pierre-Louis Bazin; Dzung L Pham
Journal:  Comput Methods Programs Biomed       Date:  2007-10-17       Impact factor: 5.428

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