Abstract
We discuss different methods and applications of model-based segmentation of medical images. In this paper model-based segmentation is defined as the assignment of labels to pixels or voxels by matching the a priori known object model to the image data. Labels may have probabilities expressing their uncertainty. Particularly we compare optimization methods with the knowledge-based system approach.
P. Suetens is also a senior research associate of the National Fund for Scientific Research, Belgium.
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© 1991 Springer-Verlag Berlin Heidelberg
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Suetens, P., Verbeeck, R., Delaere, D., Nuyts, J., Bijnens, B. (1991). Model-Based Image Segmentation: Methods and Applications. In: Stefanelli, M., Hasman, A., Fieschi, M., Talmon, J. (eds) AIME 91. Lecture Notes in Medical Informatics, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48650-0_1
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DOI: https://doi.org/10.1007/978-3-642-48650-0_1
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