Medical image segmentation using a tree model
Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136) - Tập 3 - Trang 2626-2629 vol.3
Tóm tắt
A model-driven, multiscale medical image segmentation system is presented. A tree representation is calculated for the image, using a modification of the immersion algorithm used for watersheds calculation. Segmentation is carried out by a matching process between the obtained tree and a tree model, which embeds the prior knowledge about the images. Tree matching is done in a multilevel way, processing different tree levels sequentially. For each level, an optimization process is performed, in which an error function, obtained from differences between the model and the segmented tree, is minimized. 13 parameters, concerning gray level, shape, position and connectivity, are used to characterize the objects. The model is obtained from a set of training images, assigning manual labels to tree nodes with a user interface designed especially for this purpose. Three-dimensional, multicomponent images can be processed by adapting gradient and parameter calculation. The system has been tested for intracranial cavity segmentation in magnetic resonance images, giving accurate results.
Từ khóa
#Biomedical imaging #Image segmentation #Filters #Signal processing #Gas insulated transmission lines #Shape #User interfaces #System testing #Magnetic resonance #Image analysisTài liệu tham khảo
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