Grey-Level Morphology Based Segmentation of MRI of the Human Cortex

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Venue:
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Year:
2001

Citing 0
Cited 2

Segmentation of T1-MRI of the human cortex using a 3D grey-level morphology approach

SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Segmentation of multimodal MRI of hippocampus using 3d grey-level morphology combined with artificial neural networks

SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis

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Abstract

Abstract: In this paper an algorithm for fully automatic segmentation of the cortex from T1-weighted axial or sagittal MRI data is presented. When analysing 3D MRI images of the brain it is often important to segment the brain from non-brain tissue such as eyes and membranes of the brain. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Four initial masks are created; first two thresholded masks from the original volume, background and brain tissue, then a third mask thresholded from a 3D grey-level eroded version of the volume, brain tissue, and lastly a fourth mask thresholded from a 3D grey-level dilated version of the volume, containing surrounding fat. On the start slice of these masks, binary morphological operations and logical operations are used. Then the rest of the slices are segmented using information from the previous slice combined with the other masks. Information from earlier slices is propagated to keep the segmented volume from leaking into non-brain tissue.