Logeswaran Rajasvaran
BK Digital Media Division, Department of Media (HCI Lab), College of Information Technology, Soongsil University, 1-1 Sangdo-Dong, Dongjak-Gu, Seoul 156-743, South Korea.
Comput Biol Med. 2008 Mar;38(3):391-400. doi: 10.1016/j.compbiomed.2008.01.001.
Magnetic resonance cholangio pancreatography (MRCP) has become a reference technique for biliary tree analysis. Typical MRCP images, however, suffer from difficulty in distinguishing the structure of the biliary tree in order to identify abnormalities, for clinical diagnosis. For efficiency in analysing MRCP image series, the need arises for the use of semi-automated image processing techniques. A segment-based multi-scale approach is described, incorporated with image selection, enhancement and watershed segmentation, to identify and reconstruct the hierarchical biliary tree structure in 2D MRCP images. The results achieved may be further extended to higher dimensional images.
磁共振胰胆管造影(MRCP)已成为胆管树分析的参考技术。然而,典型的MRCP图像在区分胆管树结构以识别异常用于临床诊断方面存在困难。为了提高分析MRCP图像序列的效率,需要使用半自动图像处理技术。本文描述了一种基于片段的多尺度方法,该方法结合了图像选择、增强和分水岭分割,以识别和重建二维MRCP图像中的分层胆管树结构。所取得的结果可进一步扩展到更高维度的图像。