A unifying framework for partial volume segmentation of brain MR images
- 2 April 2003
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 22 (1), 105-119
- https://doi.org/10.1109/tmi.2002.806587
Abstract
Accurate brain tissue segmentation by intensity-based voxel classification of magnetic resonance (MR) images is complicated by partial volume (PV) voxels that contain a mixture of two or more tissue types. In this paper, we present a statistical framework for PV segmentation that encompasses and extends existing techniques. We start from a commonly used parametric statistical image model in which each voxel belongs to one single tissue type, and introduce an additional downsampling step that causes partial voluming along the borders between tissues. An expectation-maximization approach is used to simultaneously estimate the parameters of the resulting model and perform a PV classification. We present results on well-chosen simulated images and on real MR images of the brain, and demonstrate that the use of appropriate spatial prior knowledge not only improves the classifications, but is often indispensable for robust parameter estimation as well. We conclude that general robust PV segmentation of MR brain images requires statistical models that describe the spatial distribution of brain tissues more accurately than currently available models.Keywords
This publication has 31 references indexed in Scilit:
- The Ising/Potts model is not well suited to segmentation tasksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithmIEEE Transactions on Medical Imaging, 2001
- Automated segmentation of multiple sclerosis lesions by model outlier detectionIEEE Transactions on Medical Imaging, 2001
- Convergence of a stochastic approximation version of the EM algorithmThe Annals of Statistics, 1999
- Automated model-based tissue classification of MR images of the brainIEEE Transactions on Medical Imaging, 1999
- Multiscale Segmentation of Three-Dimensional MR Brain ImagesInternational Journal of Computer Vision, 1999
- Robust partial-volume tissue classification of cerebral MRI scansPublished by SPIE-Intl Soc Optical Eng ,1997
- Intensity-Based Object Extraction from 3D Medical Images Including a Correction of Partial Volume ErrorsPublished by British Machine Vision Association and Society for Pattern Recognition ,1994
- Partial volume tissue classification of multichannel magnetic resonance images-a mixel modelIEEE Transactions on Medical Imaging, 1991
- Comments on ``Application of the Conditional Population-Mixture Model to Image Segmentation''Ieee Transactions On Pattern Analysis and Machine Intelligence, 1984