Literature DB >> 16685885

Two methods for validating brain tissue classifiers.

Marcos Martin-Fernandez1, Sylvain Bouix, Lida Ungar, Robert W McCarley, Martha E Shenton.   

Abstract

In this paper, we present an evaluation of seven automatic brain tissue classifiers based on level of agreements. A number of agreement measures are explained, and we show how they can be used to compare different segmentation techniques. We use the Simultaneous Truth and Performance Level Estimation (STAPLE) of Warfield et al. but also introduce a novel evaluation technique based on the Williams' index. The methods are evaluated using these two techniques on a population of forty subjects, each having an SPGR scan and a co-registered T2 weighted scan. We provide an interpretation of the results and show how similar the output of the STAPLE analysis and Williams' index are. When no ground truth is required, we recommend the use of Williams' index as it is easy and fast to compute.

Mesh:

Year:  2005        PMID: 16685885      PMCID: PMC2775440          DOI: 10.1007/11566465_64

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  12 in total

1.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.

Authors:  Y Zhang; M Brady; S Smith
Journal:  IEEE Trans Med Imaging       Date:  2001-01       Impact factor: 10.048

2.  Flux-based anisotropic diffusion applied to enhancement of 3-D angiogram.

Authors:  Karl Krissian
Journal:  IEEE Trans Med Imaging       Date:  2002-11       Impact factor: 10.048

3.  Improved watershed transform for medical image segmentation using prior information.

Authors:  V Grau; A U J Mewes; M Alcañiz; R Kikinis; S K Warfield
Journal:  IEEE Trans Med Imaging       Date:  2004-04       Impact factor: 10.048

4.  Adaptive segmentation of MRI data.

Authors:  W M Wells; W L Grimson; R Kikinis; F A Jolesz
Journal:  IEEE Trans Med Imaging       Date:  1996       Impact factor: 10.048

5.  A Computer Program for Classifying Plants.

Authors:  D J Rogers; T T Tanimoto
Journal:  Science       Date:  1960-10-21       Impact factor: 47.728

6.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

Authors:  J G Sled; A P Zijdenbos; A C Evans
Journal:  IEEE Trans Med Imaging       Date:  1998-02       Impact factor: 10.048

7.  Multi-modal volume registration by maximization of mutual information.

Authors:  W M Wells; P Viola; H Atsumi; S Nakajima; R Kikinis
Journal:  Med Image Anal       Date:  1996-03       Impact factor: 8.545

8.  Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis.

Authors:  Alex P Zijdenbos; Reza Forghani; Alan C Evans
Journal:  IEEE Trans Med Imaging       Date:  2002-10       Impact factor: 10.048

9.  Three validation metrics for automated probabilistic image segmentation of brain tumours.

Authors:  Kelly H Zou; William M Wells; Ron Kikinis; Simon K Warfield
Journal:  Stat Med       Date:  2004-04-30       Impact factor: 2.373

Review 10.  Fast robust automated brain extraction.

Authors:  Stephen M Smith
Journal:  Hum Brain Mapp       Date:  2002-11       Impact factor: 5.038

View more
  4 in total

1.  On evaluating brain tissue classifiers without a ground truth.

Authors:  Sylvain Bouix; Marcos Martin-Fernandez; Lida Ungar; Motoaki Nakamura; Min-Seong Koo; Robert W McCarley; Martha E Shenton
Journal:  Neuroimage       Date:  2007-04-25       Impact factor: 6.556

2.  Statistical framework for validation without ground truth of choroidal thickness changes detection.

Authors:  Tiziano Ronchetti; Christoph Jud; Peter M Maloca; Selim Orgül; Alina T Giger; Christoph Meier; Hendrik P N Scholl; Rachel Ka Man Chun; Quan Liu; Chi-Ho To; Boris Považay; Philippe C Cattin
Journal:  PLoS One       Date:  2019-06-28       Impact factor: 3.240

3.  High resolution multidetector CT-aided tissue analysis and quantification of lung fibrosis.

Authors:  Vanessa A Zavaletta; Brian J Bartholmai; Richard A Robb
Journal:  Acad Radiol       Date:  2007-07       Impact factor: 3.173

4.  Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

Authors:  Jingxin Nie; Zhong Xue; Tianming Liu; Geoffrey S Young; Kian Setayesh; Lei Guo; Stephen T C Wong
Journal:  Comput Med Imaging Graph       Date:  2009-05-14       Impact factor: 4.790

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.