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A Study of Computer Aided Visualization and Quantification of Emphysema

机译:气肿的计算机辅助可视化和量化研究

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Emphysema is a lung disease that occurs as more and more of the walls between air sacs in the lungs get destroyed. Computed tomography (CT) image of the human thorax has been a useful modality for assessing emphysema. Out goal in this paper is to automatically visualize bullaes (continuous low-attenuated region in CT which represents the air-filled region in the CT and therefore the emphyseinatous lesion in the lung) in the lungs in three dimensions and quantify the emphysema severity of each bullae based on its size and the distance of the bullae from the center of the lungs using fuzzy logic. From the computed emphysema severity score of bullae in the lung, we calculate the overall emphysema severity of the lung by summing up the emphysema severity score of all bullaes in the lung. For the visualization part, we first compute a transparent three-dimensional lung model and from there, we cluster the bullaes using K-means clustering method to see how the bullaes are distributed in groups in the lung. Besides, we compress the three-dimensional lung model along x-, y- and z-axis by assigning the value of every bullae pixel as one and adding up the pixel intensity along x-, y- and z-axis allowing the visualization of the compressed lung from the front, side, and top view, respectively. Consequently, we color the compressed image using continuous multi-valued color code for indicating the severity of the emphysematous destruction in the lung. Our visualization techniques can be used as a medical assistant visualization tool for radiologists.
机译:肺气肿是一种肺部疾病,随着肺中气囊之间越来越多的壁被破坏而发生。人胸部的计算机断层扫描(CT)图像已成为评估肺气肿的一种有用方法。本文的最终目标是在三个维度上自动可视化肺中的大疱(CT中的连续低衰减区域,代表CT中的空气填充区域,因此代表肺中的肺气肿性病变),并对每个肺气肿的严重程度进行量化使用模糊逻辑,根据大疱的大小和大疱与肺中心的距离来确定大疱。根据肺中大疱的肺气肿严重程度得分,我们通过汇总肺中所有大疱的肺气肿严重程度得分,计算出肺的总体肺气肿严重程度。对于可视化部分,我们首先计算一个透明的三维肺模型,然后从那里开始,使用K-means聚类方法对Bulla进行聚类,以查看Bulla如何在肺中成组分布。此外,我们通过将每个大疱像素的值分配为1并沿x,y和z轴相加像素强度,从而沿x,y和z轴压缩三维肺模型。从正面,侧面和顶视图分别观察压缩的肺部。因此,我们使用连续的多值颜色代码对压缩图像进行着色,以指示肺气肿破坏的严重程度。我们的可视化技术可以用作放射科医生的医疗助手可视化工具。

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