Integration of structural and functional data

Duncan, John S.; Fish, D. R.

doi:10.1097/00019052-199804000-00007

Cited by 6 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Functional imaging parameters need to be interpreted with reference to structural imaging data [Duncan and Fish, 1998]. For single subjects, correspondence between structure and function can be obtained through coregistration of functional imaging data with high-resolution structural imaging, typically magnetic resonance imaging (MRI).…”

Section: Introductionmentioning

confidence: 99%

Three‐dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe

Hammers

Allom

Koepp

et al. 2003

Human Brain Mapping

Self Cite

1,118

918

View full text Add to dashboard Cite

Probabilistic atlases of neuroanatomy are more representative of population anatomy than single brain atlases. They allow anatomical labeling of the results of group studies in stereotaxic space, automated anatomical labeling of individual brain imaging datasets, and the statistical assessment of normal ranges for structure volumes and extents. No such manually constructed atlas is currently available for the frequently studied group of young adults. We studied 20 normal subjects (10 women, median age 31 years) with high-resolution magnetic resonance imaging (MRI) scanning. Images were nonuniformity corrected and reoriented along both the anterior-posterior commissure (AC-PC) line horizontally and the midsagittal plane sagittally. Building on our previous work, we have expanded and refined existing algorithms for the subdivision of MRI datasets into anatomical structures. The resulting algorithm is presented in the Appendix. Forty-nine structures were interactively defined as three-dimensional volumes-of-interest (VOIs). The resulting 20 individual atlases were spatially transformed (normalized) into standard stereotaxic space, using SPM99 software and the MNI/ICBM 152 template. We evaluated volume data for all structures both in native space and after spatial normalization, and used the normalized superimposed atlases to create a maximum probability map in stereotaxic space, which retains quantitative information regarding inter-subject variability. Its potential applications range from the automatic labeling of new scans to the detection of anatomical abnormalities in patients. Further data can be extracted from the atlas for the detailed analysis of individual structures.

show abstract

Section: Introductionmentioning

confidence: 99%