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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Automatic Inference of Sulcus Patterns Using 3D Moment Invariants
verfasst von : Z. Y. Sun, D. Rivière, F. Poupon, J. Régis, J. -F. Mangin
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
Verlag: Springer Berlin Heidelberg
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The goal of this work is the automatic inference of frequent patterns of the cortical sulci, namely patterns that can be observed only for a subset of the population. The sulci are detected and identified using brainVISA open software. Then, each sulcus is represented by a set of shape descriptors called the 3D moment invariants. Unsupervised agglomerative clustering is performed to define the patterns. A ratio between compactness and contrast among clusters is used to select the best patterns. A pattern is considered significant when this ratio is statistically better than the ratios obtained for clouds of points following a Gaussian distribution. The patterns inferred for the left cingulate sulcus are consistent with the patterns described in the atlas of Ono.