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Algorithm of Pulmonary Emphysema Extraction Using Low Dose Thoracic 3-D CT Images

机译:低剂量胸腔3-D CT图像提取肺气肿的算法

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摘要

Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to 100 thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.
机译:最近,由于衰老和吸烟,肺气肿患者正在增加。由于肺气肿破坏的肺泡无法修复,因此需要尽早发现肺气肿。我们描述了一种提取气肿性病变的定量算法,并使用低剂量胸腔3-D CT图像定量评估了它们的分布模式。该算法确定了肺部解剖结构,并提取了低衰减区域(LAA)作为气肿性病变的候选者。将算法应用于100例胸部3-D CT图像,然后通过后续3-D CT图像,我们证明了其潜在的有效性,可帮助放射科医生和医生定量评估气肿性病变的分布及其在时间间隔变化中的演变。

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