BACKGROUND Accurate measurement and reconstruction of orbital soft tissue is important to diagnosis and treatment of orbital diseases. This study applied an interactive graph cut method to orbital soft tissue precise segmentation and calculation in computerized tomography (CT) images, and to estimate its application in orbital reconstruction. METHODS The interactive graph cut method was introduced to segment extraocular muscle and intraorbital fat in CT images. Intra- and inter-observer variability of tissue volume measured by graph cut segmentation was validated. Accuracy and reliability of the method was accessed by comparing with manual delineation and commercial medical image software. Intraorbital structure of 10 patients after enucleation surgery was reconstructed based on graph cut segmentation and soft tissue volume were compared within two different surgical techniques. RESULTS Both muscle and fat tissue segmentation results of graph cut method showed good consistency with ground truth in phantom data. There were no significant differences in muscle calculations between observers or segmental methods (p > 0.05). Graph cut results of fat tissue had coincidental variable trend with ground truth which could identify 0.1cm3 variation. The mean performance time of graph cut segmentation was significantly shorter than manual delineation and commercial software (p < 0.001). Jaccard similarity and Dice coefficient of graph cut method were 0.767 ± 0.045 and 0.836 ± 0.032 for human normal extraocular muscle segmentation. The measurements of fat tissue were significantly better in graph cut than those in commercial software (p < 0.05). Orbital soft tissue volume was decreased in post-enucleation orbit than that in normal orbit (p < 0.05). CONCLUSION The graph cut method was validated to have good accuracy, reliability and efficiency in orbit soft tissue segmentation. It could discern minor volume changes of soft tissue. The interactive segmenting technique would be a valuable tool for dynamic analysis and prediction of therapeutic effect and orbital reconstruction.

中文翻译：

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去核后眼眶重建的准确的交互式分割和眼眶软组织的体积计算。

背景技术准确测量和重建眼眶软组织对于眼眶疾病的诊断和治疗很重要。这项研究将交互式图割方法应用于计算机断层扫描（CT）图像中的眼眶软组织精确分割和计算，并评估其在眼眶重建中的应用。方法采用交互式图切法对CT图像中眼外肌和眶内脂肪进行分割。验证了观察者内部和观察者之间通过图切分割测量的组织体积的变异性。通过与手动描绘和商业医学图像软件进行比较，获得了该方法的准确性和可靠性。根据图切分法重建了去核手术后10例患者的眶内结构，并在两种不同的手术技术中比较了软组织的体积。结果图割法的肌肉和脂肪组织分割结果均与幻像数据的地面真实性具有良好的一致性。观察者之间或分段方法之间的肌肉计算没有显着差异（p> 0.05）。脂肪组织的图形切割结果具有与地面真实性的同时变化趋势，可以识别出0.1cm3的变化。图形切割分割的平均执行时间明显短于手动勾画和商业软件（p <0.001）。人正常眼外肌分割的Jaccard相似度和图切方法的Dice系数分别为0.767±0.045和0.836±0.032。在图割中，脂肪组织的测量结果明显优于商业软件（p <0.05）。摘除后眼眶的软组织体积比正常眼眶减小（p <0.05）。结论验证了图割法在眼眶软组织分割中具有良好的准确性，可靠性和效率。它可以识别出软组织的微小体积变化。交互式分割技术将是用于动态分析和预测治疗效果以及眼眶重建的有价值的工具。眼眶软组织分割的可靠性和效率。它可以识别出软组织的微小体积变化。交互式分割技术将是用于动态分析和预测治疗效果以及眼眶重建的有价值的工具。眼眶软组织分割的可靠性和效率。它可以识别出软组织的微小体积变化。交互式分割技术将是用于动态分析和预测治疗效果以及眼眶重建的有价值的工具。