Automatic Brain Tissue Extraction Method Using Erosion-Dilation Treatment (BREED) From Three-Dimensional Magnetic Resonance Imaging T1-Weighted Data

To improve the efficiency of brain image analysis, we propose a full-automatic method for extracting brain tissue from three-dimensional magnetic resonance imaging of T1-weighted data on the human head (brain tissue extraction method using erosion-dilation treatment [BREED]). The extraction processing is realized by combining signal intensity thresholding by means of the discriminant analysis method and an erosion-dilation treatment of the image. The accuracy of BREED is evaluated using both simulated and subject data. BREED can extract brain tissues with high accuracy (approximately 97%) for either simulated or subject data.

[1]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  W. A. Hanson,et al.  Interactive 3D segmentation of MRI and CT volumes using morphological operations. , 1992, Journal of computer assisted tomography.

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

[4]  D. Louis Collins,et al.  Automatic 3‐D model‐based neuroanatomical segmentation , 1995 .

[5]  W. Eric L. Grimson,et al.  Adaptive Segmentation of MRI Data , 1995, CVRMed.

[6]  W. Eric L. Grimson,et al.  Segmentation of brain tissue from magnetic resonance images , 1995, Medical Image Anal..

[7]  Alan C. Evans,et al.  An Extensible MRI Simulator for Post-Processing Evaluation , 1996, VBC.

[8]  Alan C. Evans,et al.  BrainWeb: Online Interface to a 3D MRI Simulated Brain Database , 1997 .

[9]  D. Louis Collins,et al.  Design and construction of a realistic digital brain phantom , 1998, IEEE Transactions on Medical Imaging.

[10]  N. Makris,et al.  Gyri of the human neocortex: an MRI-based analysis of volume and variance. , 1998, Cerebral cortex.

[11]  M. Stella Atkins,et al.  Fully automatic segmentation of the brain in MRI , 1998, IEEE Transactions on Medical Imaging.

[12]  David N. Kennedy,et al.  Semiautomatic segmentation of brain exterior in magnetic resonance images driven by empirical procedures and anatomical knowledge , 1998, Medical Image Anal..

[13]  Alan C. Evans,et al.  MRI Simulation Based Evaluation and Classifications Methods , 1999, IEEE Trans. Medical Imaging.

[14]  Benoit M. Dawant,et al.  Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects , 1999, IEEE Transactions on Medical Imaging.

[15]  A. Evans,et al.  MRI simulation-based evaluation of image-processing and classification methods , 1999, IEEE Transactions on Medical Imaging.

[16]  Koenraad Van Leemput,et al.  Automated model-based tissue classification of MR images of the brain , 1999, IEEE Transactions on Medical Imaging.

[17]  G. Hagemann,et al.  Fast, accurate, and reproducible automatic segmentation of the brain in T1‐weighted volume MRI data , 1999, Magnetic resonance in medicine.

[18]  Alan C. Evans,et al.  Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.

[19]  Max A. Viergever,et al.  Automatic Morphology-Based Brain Segmentation (MBRASE) from MRI-T1 Data , 2000, NeuroImage.

[20]  T. Schormann,et al.  Hemispheric Shape of European and Japanese Brains: 3-D MRI Analysis of Intersubject Variability, Ethnical, and Gender Differences , 2001, NeuroImage.

[21]  Arnold W. M. Smeulders,et al.  Interaction in the segmentation of medical images: A survey , 2001, Medical Image Anal..