학술논문

Robust extraction of urinary stones from CT data using attribute filters
Document Type
Conference
Source
2009 16th IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2009 16th IEEE International Conference on. :2629-2632 Nov, 2009
Subject
Computing and Processing
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Robustness
Data mining
Filters
Biomedical imaging
Computed tomography
Surface morphology
Active contours
Shape
Filtering
Bladder
Urinary stones
attribute filters
sphericity
Language
ISSN
1522-4880
2381-8549
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.