Literature DB >> 12594719

Accuracy and reproducibility of manual and semiautomated quantification of MS lesions by MRI.

Edward A Ashton1, Chihiro Takahashi, Michel J Berg, Andrew Goodman, Saara Totterman, Sven Ekholm.   

Abstract

PURPOSE: To evaluate the accuracy, reproducibility, and speed of two semiautomated methods for quantifying total white matter lesion burden in multiple sclerosis (MS) patients with respect to manual tracing and to other methods presented in recent literature.
MATERIALS AND METHODS: Two methods involving the use of MRI for semiautomated quantification of total lesion burden in MS patients were examined. The first method, geometrically constrained region growth (GEORG), requires user specification of lesion location. The second technique, directed multispectral segmentation (DMSS), requires only the location of a single exemplar lesion. Test data sets included both clinical MS data and MS brain phantoms.
RESULTS: The mean processing times were 60 minutes for manual tracing, 10 minutes for region growth, and 3 minutes for directed segmentation. Intra- and interoperator coefficients of variation (CVs) were 5.1% and 16.5% for manual tracing, 1.4% and 2.3% for region growth, and 1.5% and 5.2% for directed segmentation. The average deviations from manual tracing were 9% for region growth and 5.7% for directed segmentation.
CONCLUSION: Both semiautomated methods were shown to have a significant advantage over manual tracing in terms of speed and precision. The accuracy of both methods was acceptable, given the high variability of the manual results. Copyright 2003 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2003        PMID: 12594719     DOI: 10.1002/jmri.10258

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


  36 in total

1.  Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland.

Authors:  Diane M Renz; Horst K Hahn; Peter Schmidt; Jan Rexilius; Markus Lentschig; Alexander Pfeil; Dieter Sauner; Clemens Fitzek; Hans-Joachim Mentzel; Werner A Kaiser; Jürgen R Reichenbach; Joachim Böttcher
Journal:  Neuroradiology       Date:  2010-06-19       Impact factor: 2.804

2.  Foibles, follies, and fusion: web-based collaboration for medical image labeling.

Authors:  Bennett A Landman; Andrew J Asman; Andrew G Scoggins; John A Bogovic; Joshua A Stein; Jerry L Prince
Journal:  Neuroimage       Date:  2011-08-02       Impact factor: 6.556

3.  Automated segmentation of chronic stroke lesions using LINDA: Lesion identification with neighborhood data analysis.

Authors:  Dorian Pustina; H Branch Coslett; Peter E Turkeltaub; Nicholas Tustison; Myrna F Schwartz; Brian Avants
Journal:  Hum Brain Mapp       Date:  2016-01-12       Impact factor: 5.038

4.  Diffusion tensor imaging segmentation of white matter structures using a Reproducible Objective Quantification Scheme (ROQS).

Authors:  Sumit N Niogi; Pratik Mukherjee; Bruce D McCandliss
Journal:  Neuroimage       Date:  2007-01-04       Impact factor: 6.556

5.  CT-based manual segmentation and evaluation of paranasal sinuses.

Authors:  S Pirner; K Tingelhoff; I Wagner; R Westphal; M Rilk; F M Wahl; F Bootz; Klaus W G Eichhorn
Journal:  Eur Arch Otorhinolaryngol       Date:  2008-08-21       Impact factor: 2.503

6.  Robust statistical fusion of image labels.

Authors:  Bennett A Landman; Andrew J Asman; Andrew G Scoggins; John A Bogovic; Fangxu Xing; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2011-10-14       Impact factor: 10.048

7.  Can fully automated detection of corticospinal tract damage be used in stroke patients?

Authors:  Nancy Kou; Chang-hyun Park; Mohamed L Seghier; Alexander P Leff; Nick S Ward
Journal:  Neurology       Date:  2013-05-08       Impact factor: 9.910

Review 8.  Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

Authors:  Koji Sakai; Kei Yamada
Journal:  Jpn J Radiol       Date:  2018-11-29       Impact factor: 2.374

Review 9.  Neuroimaging in aphasia treatment research: quantifying brain lesions after stroke.

Authors:  Jenny Crinion; Audrey L Holland; David A Copland; Cynthia K Thompson; Argye E Hillis
Journal:  Neuroimage       Date:  2012-07-27       Impact factor: 6.556

10.  The left superior temporal gyrus is a shared substrate for auditory short-term memory and speech comprehension: evidence from 210 patients with stroke.

Authors:  Alexander P Leff; Thomas M Schofield; Jennifer T Crinion; Mohamed L Seghier; Alice Grogan; David W Green; Cathy J Price
Journal:  Brain       Date:  2009-12       Impact factor: 13.501

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.