Development and comparison of projection and image space 3D nodule insertion techniques

M. Robins, J. Solomon, P. Sahbaee, E. Samei
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引用次数: 5

Abstract

This study aimed to develop and compare two methods of inserting computerized virtual lesions into CT datasets. 24 physical (synthetic) nodules of three sizes and four morphologies were inserted into an anthropomorphic chest phantom (LUNGMAN, KYOTO KAGAKU). The phantom was scanned (Somatom Definition Flash, Siemens Healthcare) with and without nodules present, and images were reconstructed with filtered back projection and iterative reconstruction (SAFIRE) at 0.6 mm slice thickness using a standard thoracic CT protocol at multiple dose settings. Virtual 3D CAD models based on the physical nodules were virtually inserted (accounting for the system MTF) into the nodule-free CT data using two techniques. These techniques include projection-based and image-based insertion. Nodule volumes were estimated using a commercial segmentation tool (iNtuition, TeraRecon, Inc.). Differences were tested using paired t-tests and R2 goodness of fit between the virtually and physically inserted nodules. Both insertion techniques resulted in nodule volumes very similar to the real nodules (<3% difference) and in most cases the differences were not statistically significant. Also, R2 values were all <0.97 for both insertion techniques. These data imply that these techniques can confidently be used as a means of inserting virtual nodules in CT datasets. These techniques can be instrumental in building hybrid CT datasets composed of patient images with virtually inserted nodules.
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投影与图像空间三维结节插入技术的发展与比较
本研究旨在发展和比较两种将计算机虚拟病变插入CT数据集的方法。将24个三种大小和四种形态的物理(合成)结节插入拟人化胸假体(LUNGMAN, KYOTO KAGAKU)。对存在或不存在结节的幻体进行扫描(Somatom Definition Flash, Siemens Healthcare),并使用标准胸部CT方案,在多个剂量设置下,以0.6 mm的切片厚度通过滤波后投影和迭代重建(SAFIRE)重建图像。使用两种技术将基于物理结节的虚拟三维CAD模型(占系统MTF)虚拟插入到无结节的CT数据中。这些技术包括基于投影的插入和基于图像的插入。使用商业分割工具(iNtuition, TeraRecon, Inc.)估计结节体积。使用配对t检验和R2拟合优度来检验虚拟和物理插入结节之间的差异。两种插入技术所得到的结节体积与真实结节非常相似(差异<3%),在大多数情况下,差异无统计学意义。两种插入技术的R2值均<0.97。这些数据表明,这些技术可以作为在CT数据集中插入虚拟结节的一种手段。这些技术有助于建立混合CT数据集,这些数据集由虚拟插入结节的患者图像组成。
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