Robust extraction of urinary stones from CT data using attribute filters

Authors:
Georgios K. Ouzounis;Stilianos Giannakopoulos;Constantinos E. Simopoulos;Michael H. F. Wilkinson
Affiliations:
School of Medicine, Democritus University of Thrace, University General Hospital of Alexandroupoli, Alexandroupoli, Greece;School of Medicine, Democritus University of Thrace, University General Hospital of Alexandroupoli, Alexandroupoli, Greece;School of Medicine, Democritus University of Thrace, University General Hospital of Alexandroupoli, Alexandroupoli, Greece;Institute of Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In medical imaging, anatomical and other structures such as urinary stones, are often extracted with the aid of active contour/ surface models. Active surface-based methods have robustness limitations and are computationally expensive. In this paper we present a morphological method based on attribute filters and the newly presented sphericity attribute. The operators involved, extract the targeted objects in their entirety without shape/size distortions and proceed rapidly. Experiments on three real 3D data-sets demonstrate their efficiency and their performance is discussed.