Statistical shape model based segmentation of medical images.
This paper reviews several kinds of 2D shape representations by a set of parameters based on labeled points, Fourier descriptors and wavelet descriptors. Seven shape models for axial slices of spinal vertebra are derived by a statistical analysis of parameters corresponding to a set of example shapes and are subsequently compared. Two of the developed models are incorporated into methods for interactive segmentation of 2D gray level images. The first method is founded on Fourier descriptors, the second one is based on normalized sets of labeled points. Both methods are based on a model guided shape exploration.
University of the Federal Armed Forces Hamburg, Germany.
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Neumann
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Lorenz
D003627:Data Interpretation, Statistical; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015233:Models, Statistical; D013131:Spine / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed