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Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation

机译:广义像素剖析和比较分割在动静脉畸形分割中的应用

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摘要

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.
机译:从血管的3D图像中提取结构和几何信息是众所周知的并且被广泛解决的分割问题。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。但是,解决AVM内部结构分割问题的技术很少。在这项工作中,我们提出了一种新颖的像素剖析方法,并将其应用于3-D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可变性的情况下脱颖而出。我们方法的另一个优点是参数是自动设置的,几乎不需要人工干预。幻像和真实数据的结果证明了其有效性和潜力,可以很好地描绘AVM结构。

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