Automatic segmentation of the bladder using deformable models

被引:6
作者
Costa, Maria Jimena
Delingette, Herve
Ayache, Nicholas
机构
来源
2007 4TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING : MACRO TO NANO, VOLS 1-3 | 2007年
关键词
D O I
10.1109/ISBI.2007.356999
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
We are interested in the fully automatic delineation of the bladder in CT images in the frame of dose calculation for conformational radiotherapy. To this end we fit a series of 3D deformable templates to the contours of anatomical structures. The novelty of our approach resides in the ability to automatically adapt to different kinds of bladder images (homogenous, non-homogenous, contrasted or non-contrasted). The adaptation of the algorithm to inhomogeneities within the bladder improves the accuracy of the segmentation. We validate our approach on a database of tomodensitometric (CT) images of the lower abdomen of male patients.
引用
收藏
页码:904 / 907
页数:4
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