Literature DB >> 1446105

Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging.

R Kikinis1, M E Shenton, G Gerig, J Martin, M Anderson, D Metcalf, C R Guttmann, R W McCarley, W Lorensen, H Cline.   

Abstract

A computerized system for processing spin-echo magnetic resonance (MR) imaging data was implemented to estimate whole brain (gray and white matter) and cerebrospinal fluid volumes and to display three-dimensional surface reconstructions of specified tissue classes. The techniques were evaluated by assessing the radiometric variability of MR volume data and by comparing automated and manual procedures for measuring tissue volumes. Results showed (a) the homogeneity of the MR data and (b) that automated techniques were consistently superior to manual techniques. Both techniques, however, were affected by the complexity of the structure, with simpler structures (eg, the intracranial cavity) showing less variability and better spatial correlation of segmentation results between raters. Moreover, the automated techniques were completed for whole brain in a fraction of the time required to complete the equivalent segmentation manually. Additional evaluations included interrater reliability and an evaluation that included longitudinal measurement, in which one subject was imaged sequentially 24 times, with reliability computed from data collected by three raters over 1 year. Results showed good reliability for the automated segmentation procedures.

Mesh:

Year:  1992        PMID: 1446105     DOI: 10.1002/jmri.1880020603

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  33 in total

1.  Integrated volume visualization of functional image data and anatomical surfaces using normal fusion.

Authors:  R Stokking; K J Zuiderveld; M A Viergever
Journal:  Hum Brain Mapp       Date:  2001-04       Impact factor: 5.038

Review 2.  MRI anatomy of schizophrenia.

Authors:  R W McCarley; C G Wible; M Frumin; Y Hirayasu; J J Levitt; I A Fischer; M E Shenton
Journal:  Biol Psychiatry       Date:  1999-05-01       Impact factor: 13.382

3.  Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.

Authors:  Simon K Warfield; Kelly H Zou; William M Wells
Journal:  IEEE Trans Med Imaging       Date:  2004-07       Impact factor: 10.048

4.  Novel whole brain segmentation and volume estimation using quantitative MRI.

Authors:  J West; J B M Warntjes; P Lundberg
Journal:  Eur Radiol       Date:  2011-11-24       Impact factor: 5.315

5.  Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder.

Authors:  T V Gurvits; M E Shenton; H Hokama; H Ohta; N B Lasko; M W Gilbertson; S P Orr; R Kikinis; F A Jolesz; R W McCarley; R K Pitman
Journal:  Biol Psychiatry       Date:  1996-12-01       Impact factor: 13.382

Review 6.  A review of the automated detection of change in serial imaging studies of the brain.

Authors:  Julia Patriarche; Bradley Erickson
Journal:  J Digit Imaging       Date:  2004-06-29       Impact factor: 4.056

7.  A hierarchical algorithm for MR brain image parcellation.

Authors:  Kilian M Pohl; Sylvain Bouix; Motoaki Nakamura; Torsten Rohlfing; Robert W McCarley; Ron Kikinis; W Eric L Grimson; Martha E Shenton; William M Wells
Journal:  IEEE Trans Med Imaging       Date:  2007-09       Impact factor: 10.048

8.  An open source multivariate framework for n-tissue segmentation with evaluation on public data.

Authors:  Brian B Avants; Nicholas J Tustison; Jue Wu; Philip A Cook; James C Gee
Journal:  Neuroinformatics       Date:  2011-12

9.  Age-related total gray matter and white matter changes in normal adult brain. Part II: quantitative magnetization transfer ratio histogram analysis.

Authors:  Yulin Ge; Robert I Grossman; James S Babb; Marcie L Rabin; Lois J Mannon; Dennis L Kolson
Journal:  AJNR Am J Neuroradiol       Date:  2002-09       Impact factor: 3.825

10.  A majority rule approach for region-of-interest-guided streamline fiber tractography.

Authors:  L M Colon-Perez; W Triplett; A Bohsali; M Corti; P T Nguyen; C Patten; T H Mareci; C C Price
Journal:  Brain Imaging Behav       Date:  2016-12       Impact factor: 3.978

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