Suppr超能文献

磁共振血管造影中小血管的灰度骨架化

Gray-scale skeletonization of small vessels in magnetic resonance angiography.

作者信息

Yim P J, Choyke P L, Summers R M

机构信息

Clinical Center, NIH, Bethesda, MD 20892, USA.

出版信息

IEEE Trans Med Imaging. 2000 Jun;19(6):568-76. doi: 10.1109/42.870662.

Abstract

Interpretation of magnetic resonance angiography (MRA) is problematic due to complexities of vascular shape and to artifacts such as the partial volume effect. We present new methods to assist in the interpretation of MRA. These include methods for detection of vessel paths and for determination of branching patterns of vascular trees. They are based on the ordered region growing (ORG) algorithm that represents the image as an acyclic graph, which can be reduced to a skeleton by specifying vessel endpoints or by a pruning process. Ambiguities in the vessel branching due to vessel overlap are effectively resolved by heuristic methods that incorporate a priori knowledge of bifurcation spacing. Vessel paths are detected at interactive speeds on a 500-MHz processor using vessel endpoints. These methods apply best to smaller vessels where the image intensity peaks at the center of the lumen which, for the abdominal MRA, includes vessels whose diameter is less than 1 cm.

摘要

由于血管形状的复杂性以及诸如部分容积效应等伪影,磁共振血管造影(MRA)的解读存在问题。我们提出了有助于MRA解读的新方法。这些方法包括检测血管路径和确定血管树分支模式的方法。它们基于有序区域生长(ORG)算法,该算法将图像表示为无环图,通过指定血管端点或通过修剪过程可将其简化为骨架。通过结合分叉间距先验知识的启发式方法,有效地解决了由于血管重叠导致的血管分支模糊性问题。使用血管端点在500 MHz处理器上以交互速度检测血管路径。这些方法最适用于较小的血管,在腹部MRA中,这些血管的图像强度在管腔中心达到峰值,包括直径小于1 cm的血管。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验