Automatic contextual segmentation for imaging bones for osteopor

Details Automatic contextual segmentation for imaging bones for osteopor Automatic contextual segmentation for imaging bones for osteopor

1996-06-13

2000-02-01

Johns, Andrew W.

Image analysis

Applications

Biomedical applications

382257, G06K 900

Patent

active

060212136

ABSTRACT:
An automatic contextual segmentation method which can be used to identify features in QCT images of femora, tibiae and vertebrae. The principal advantages of this automatic approach over traditional techniques such as histomorphometry are, 1) the algorithms can be implemented in a fast, uniform, non-subjective manner across many images allowing unbiased comparisons of therapeutic efficacy, 2) much larger volumes in the region of interest can be analyzed, and 3) QCT can be used longitudinally. Two automatic contextual segmentation algorithms relate to a cortical bone algorithm (CBA) and a whole bone algorithm (WBA). These methods include a preprocessing step, a threshold selection step, a segmentation step satisfying logical constraints, a pixel wise label image updating step, and a feature extraction step; with the WBA including whole bone segmentation, cortical segmentation, spine segmentation, and centrum segmentation. The algorithms are constructed to provide successful segmentations for known classes of bones with known topological constraints.

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