Department of Telecommunications and Information Processing/TELIN-IPI-IBBT, Faculty of Engineering, Ghent University, Sint-Pietersnieuwstraat 41, 0 Ghent, Belgium.
Med Image Anal. 2012 Jul;16(5):991-1002. doi: 10.1016/j.media.2012.02.006. Epub 2012 Feb 22.
Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure.
从血管的 3D 图像中提取结构和几何信息是一个众所周知且广泛研究的分割问题。脑血管的分割在诊断和临床应用中非常重要，特别是在动静脉畸形（AVM）的诊断和手术中。然而，针对 AVM 内部结构分割问题的技术却很少。在这项工作中，我们提出了一种新的像素分析方法，并将其应用于 3D 血管造影 AVM 图像的分割。我们的算法在低分辨率图像和像素强度高度变化的情况下表现出色。我们的方法的另一个优点是参数可以自动设置，这减少了用户的手动干预。在体模和真实数据上的结果证明了它在精细描绘 AVM 结构方面的有效性和潜力。
