Comparison study of clinical 3D MRI brain segmentation evaluation

Although numerous methods to segment brain MRI for extraction of white matter, gray matter and cerebrospinal fluid (CSF) have been proposed for the past two decades, little work has been done to evaluate and compare the performance of different segmentation methods on real clinical data sets, especially for CSF. This study focuses on the comparison of the four following methods for segmentation of cerebral brain MRI: gray levels thresholding, three-dimensional level set, fuzzy connectedness and FSL. Quantitative evaluation of segmentation accuracy was performed with comparison to manual segmentation on a database of 10 adult subjects.

[1]  Hartmut Dickhaus,et al.  A deformable digital brain atlas system according to Talairach and Tournoux , 2004, Medical Image Anal..

[2]  Ting Song,et al.  Segmentation and quantitative evaluation of brain MRI data with a multiphase 3D implicit deformable model , 2004, SPIE Medical Imaging.

[3]  Supun Samarasekera,et al.  Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation , 1996, CVGIP Graph. Model. Image Process..

[4]  Robert T. Schultz,et al.  Segmentation and Measurement of the Cortex from 3D MR Images , 1998, MICCAI.

[5]  R. Kikinis,et al.  Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging , 1992, Journal of magnetic resonance imaging : JMRI.

[6]  Jeffrey C. Lagarias,et al.  Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions , 1998, SIAM J. Optim..

[7]  Ting Song,et al.  Multi-phase Three-Dimensional Level Set Segmentation of Brain MRI , 2004, MICCAI.

[8]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[9]  Jayaram K. Udupa,et al.  Methodology for evaluating image-segmentation algorithms , 2002, SPIE Medical Imaging.

[10]  Baba C. Vemuri,et al.  An Accurate and Efficient Bayesian Method for Automatic Segmentation of Brain MRI , 2002, ECCV.

[11]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[12]  Segmentation and quantitative evaluation of brain MRI data with a multi-phase three-dimensional implicit deformable model , 2004 .

[13]  D. Louis Collins,et al.  Retrospective evaluation of intersubject brain registration , 2003, IEEE Transactions on Medical Imaging.