Robust extraction of urinary stones from CT data using attribute filters
Georgios K. Ouzounis, Stilianos Giannakopoulos, Constantinos E. Simopoulos, Michael H. F. Wilkinson · 2009
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.