腹主动脉瘤血栓分割的迭代模型约束图切算法

M. Freiman, S. Esses, Leo Joskowicz, J. Sosna
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引用次数: 40

摘要

我们提出了一种迭代模型约束的图切算法,用于分割腹主动脉瘤(AAA)血栓。给定主动脉腔的初始分割,我们的方法通过迭代耦合基于强度的图最小切割分割和几何参数模型拟合来自动分割血栓。该几何模型有效地约束了图最小分割不“泄漏”到附近的静脉和器官。在8个AAA CTA数据集上的实验结果显示,在2分钟的计算机时间内对AAA血栓进行了稳健的分割,平均绝对体积差为8.0%,平均体积重叠误差为12.9%,与观察者间误差相当。
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AN iterative model-constrained graph-cut algorithm for Abdominal Aortic Aneurysm thrombus segmentation
We present an iterative model-constrained graph-cut algorithm for the segmentation of Abdominal Aortic Aneurysm (AAA) thrombus. Given an initial segmentation of the aortic lumen, our method automatically segments the thrombus by iteratively coupling intensity-based graph min-cut segmentation and geometric parametric model fitting. The geometric model effectively constrains the graph min-cut segmentation from “leaking” to nearby veins and organs. Experimental results on 8 AAA CTA datasets yield robust segmentations of the AAA thrombus in 2 mins computer time with a mean absolute volume difference of 8.0% and mean volumetric overlap error of 12.9%, which is comparable to the interobserver error.
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