Automatic classification of sulcal regions of the human brain cortex using pattern recognition

Kirsten J. Behnke, Maryam E. Rettmann, Dzung L. Pham, Dinggang Shen, Susan M. Resnick, Christos Davatzikos, Jerry L. Prince

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Parcellation of the cortex has received a great deal of attention in magnetic resonance (MR) image analysis, but its usefulness has been limited by time-consuming algorithms that require manual labeling. An automatic labeling scheme is necessary to accurately and consistently parcellate a large number of brains. The large variation of cortical folding patterns makes automatic labeling a challenging problem, which cannot be solved by deformable atlas registration alone. In this work, an automated classification scheme that consists of a mix of both atlas driven and data driven methods is proposed to label the sulcal regions, which are defined as the gray matter regions of the cortical surface surrounding each sulcus. The premise for this algorithm is that sulcal regions can be classified according to the pattern of anatomical features (e.g. supramarginal gyrus, cuneus, etc.) associated with each region. Using a nearest-neighbor approach, a sulcal region is classified as being in the same class as the sulcus from a set of training data which has the nearest pattern of anatomical features. Using just one subject as training data, the algorithm correctly labeled 83% of the regions that make up the main sulci of the cortex.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsM. Sonka, J.M. Fitzpatrick
Pages1499-1510
Number of pages12
Volume5032 III
DOIs
Publication statusPublished - 2003
Externally publishedYes
EventMedical Imaging 2003: Image Processing - San Diego, CA, United States
Duration: 2003 Feb 172003 Feb 20

Other

OtherMedical Imaging 2003: Image Processing
CountryUnited States
CitySan Diego, CA
Period03/2/1703/2/20

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Keywords

  • Atlas
  • Deformable models
  • Human brain cortex
  • Pattern recognition
  • Sulcal labeling
  • Sulci

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Behnke, K. J., Rettmann, M. E., Pham, D. L., Shen, D., Resnick, S. M., Davatzikos, C., & Prince, J. L. (2003). Automatic classification of sulcal regions of the human brain cortex using pattern recognition. In M. Sonka, & J. M. Fitzpatrick (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 5032 III, pp. 1499-1510) https://doi.org/10.1117/12.480834