Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
IEEE Transactions on Pattern Analysis and Machine Intelligence
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Visualization in Medicine: Theory, Algorithms, and Applications
Visualization in Medicine: Theory, Algorithms, and Applications
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
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Interaction increases flexibility of segmentation but it leads to undesired behaviour of an algorithm if knowledge being requested is inappropriate. In region growing, this is the case for defining the homogeneity criterion as its specification depends also on image formation properties that are not known to the user. We developed a region growing algorithm that learns its homogeneity criterion automatically from characteristics of the region to be segmented. It produces results that are only little sensitive to the seed point location and it allows a segmentation of individual structures. The method was successfully tested on artificial images and on CT images.