Automatic Segmentation of Abdominal Wall in Ventral Hernia CT: A Pilot Study.
Automatic Segmentation of Abdominal Wall in Ventral Hernia CT: A Pilot Study.
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腹疝 CT 腹壁自动分割：一项试点研究。
DOI：
10.1117/12.2007060
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Landman,BennettA
中科院分区：
文献类型：
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作者：
Xu,Zhoubing;Allen,WadeM;Poulose,BenjaminK;Landman,BennettA
腹疝（VH）的治疗一直是医疗保健中的一个具有挑战性的问题。这些疝气的修复充满了失败；据报道，即使使用生物相容性补片，复发率也在24-43%之间。目前，计算机断层扫描（CT）用于指导干预，通过专家，但定性，临床判断；值得注意的是，没有使用基于图像处理的定量指标。我们建议采用图像分割方法捕捉腹壁的三维结构及其异常，为测量疝和周围组织的几何特性提供基础，从而优化干预。到目前为止，还没有自动分割算法来量化腹壁和潜在的疝。在这项初步研究中，通过对术后患者进行四次临床获得的CT扫描，我们展示了一种新的方法来对腹壁和基本腹部特征（包括骨标记和皮肤表面）进行几何分类。我们的方法采用分层设计，其中腹壁在皮肤和骨结构的背景下被隔离，使用水平集方法。基于人工标记的地面真值，对所有分割结果进行了表面误差定量验证。腹壁外表面平均表面误差小于2mm。该方法建立了腹壁特征的基线，以改善VH护理。
The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24–43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments; notably, quantitative metrics based on image-processing are not used. We propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore, to optimize intervention. To date, automated segmentation algorithms have not been presented to quantify the abdominal wall and potential hernias. In this pilot study with four clinically acquired CT scans on post-operative patients, we demonstrate a novel approach to geometric classification of the abdominal wall and essential abdominal features (including bony landmarks and skin surfaces). Our approach uses a hierarchical design in which the abdominal wall is isolated in the context of the skin and bony structures using level set methods. All segmentation results were quantitatively validated with surface errors based on manually labeled ground truth. Mean surface errors for the outer surface of the abdominal wall was less than 2mm. This approach establishes a baseline for characterizing the abdominal wall for improving VH care.