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胸部CT图像中感兴趣区域的提取与量化分析 被引量:1

Extraction of ROI and Quantitative Diagnosis of Thoracic High Resolution CT
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摘要 目的:根据临床应用需求,研究了胸部高分辨率CT图像中感兴趣区域(region of interest,ROI)的提取与量化诊断问题。方法:首先由人工勾勒感兴趣区域边界,再应用Bresenham扫描线算法生成连续的区域边界,然后,应用基于四邻域的背景标记扫描线方法,对区域外像素作出标记,从而得到选定区域。最后,计算区域的量化参数,并根据肺气肿量化诊断标准,对感兴趣区域进行分析与辅助诊断。结果:计算得到肺气肿占整个肺部容积的百分比为39.2%,该患者属于3级重度肺气肿。结论:实验证明,该方法能快速、准确地提取任意形状的区域,并对给定区域进行统计分析,非常有利于医生的准确诊断。 Objective:Based on the requirement from clinical application, extraction of ROI and quantitative diagnosis of thoracic high resolution CT are investigated. Materials and Methods:Firstly, the boundary of ROI was drawn through mouse dragging, then the Bresenham scanning line algorithm was adopted to establish consecutive boundary. Secondly, the scanning line method based on 4-neighbour background pixels marked was applied to identify pixels in the background and the selected region was then extracted. Finally, some parameters were calculated to analyze and diagnose on the ROI. Result: The calculated pulmonary emphysema area is nearly 39.2% of the whole lung area, so the patient belongs to level-3 pulmonary emphysema. Conclusion: Experiments shows that the novel method can be used to extract region with any shape accurately and effectively, analyze the ROI and make exact diagnosis.
出处 《中国医学物理学杂志》 CSCD 2008年第6期895-898,共4页 Chinese Journal of Medical Physics
关键词 高分辨率CT 感兴趣区域 区域背景标记扫描 辅助诊断 high resolution CT region of interest scanning-line method based on background pixels marked aided diagnosis
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