Format

Send to:

Choose Destination
See comment in PubMed Commons below

Brain tissue segmentation based on corrected gray-scale analysis.

Author information

  • 1Yale University School Medical Center, The Anlyan Center, 300 Cedar Street, New Haven, CT 06520, USA.

Abstract

Image signal-to-noise ratio (SNR) and signal intensity (SI) inhomogeneities are factors that strongly affect the accuracy and precision of brain tissue segmentations in magnetic resonance image (MRI). In this work, SNR and contrast of brain images are optimized by TR and inversion recovery time TI in multi-spectrum MRI data sets. SI inhomogeneities are measured in vivo using a recently developed method allowing improved correction. The three-Gaussain distribution model is used to fit histograms of the images to find the initialization parameters for an Expectation-Maximization (EM) segmentation algorithm. Compared with other methods, the field map method provides better correction of SI inhomogeneities and excellent segmentation results.

PMID:
17282881
[PubMed]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for IEEE Engineering in Medicine and Biology Society
    Loading ...
    Write to the Help Desk