Adaptive Segmentation of MRI data

Adaptive Segmentation of MRI data (1995)

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by W.M. Wells , III , W.E.L. Grimson , R. Kikinis , F. A. Jolesz

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139 - 14 self

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@MISC{Wells95adaptivesegmentation,
    author = {W.M. Wells and III and W.E.L. Grimson and R. Kikinis and F. A. Jolesz},
    title = {Adaptive Segmentation of MRI data},
    year = {1995}
}

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Abstract

Intensity-based classification of MR images has proven problematic, even when advanced techniques are used. Intra-scan and inter-scan intensity inhomogeneities are a common source of difficulty. While reported methods have had some success in correcting intra-scan inhomogeneities, such methods require supervision for the individual scan. This paper describes a new method called adaptive segmentation that uses knowledge of tissue intensity properties and intensity inhomogeneities to correct and segment MR images. Use of the EM algorithm leads to a method that allows for more accurate segmentation of tissue types as well as better visualization of MRI data, that has proven to be effective in a study that includes more than 1000 brain scans. Implementation and results are described for segmenting the brain in the following types of images: axial (dual-echo spin-echo), coronal (3DFT gradient-echo T1-weighted) all using a conventional head coil; and a sagittal section acquired using a surf...

Citations

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1	List of Figures 1 Synthetic image and results of conventional segmentation : : : : : : : : : : 25 2 Results of adaptive segmentation and bias field : : : : : : : : : : : : : : : 25 3 Original gradient-echo image. : : : : : : : : : : : : : : : : : : : : : - Schneider, Glover - 1991