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Identification and Quantification of Pulmonary Emphysema through Pseudocolors

机译:通过伪色鉴定和量化肺气肿

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Chronic Obstructive Pulmonary Disease (COPD) is a world health problem with high morbidity and mortality. High-Resolution Computed Tomography (HRCT), is an excellent tool for early detection of emphysema component of COPD. Despite this fact, HRCT presents limitations inherent to the subjective analysis of the gray scale image that directly compromises the accuracy for both diagnosis and precise determination of the disease extension. The objective of this paper is present a colored mask algorithm (CMA) to identify and quantify the emphysema, enhancing its visualization through pseudocolors. We studied 21 images of 7 patients with COPD and 1 healthy volunteer. The CMA applies colors to the segmented lungs according to pre-defined ranges of Hounsfield units. CMA automatically calculates the relative area occupied by tomographic densities within the pre-defined ranges, allowing precise quantification of diseased and normal parenchyma. Future works are needed in order to validate the incorporation of the CMA in the image assessment of emphysema in COPD patients.
机译:慢性阻塞性肺疾病(COPD)是世界性疾病,发病率和死亡率很高。高分辨率计算机断层扫描(HRCT)是早期检测COPD肺气肿成分的出色工具。尽管如此,HRCT仍呈现出灰度图像主观分析固有的局限性,这直接损害了疾病扩展的诊断和精确确定的准确性。本文的目的是提出一种彩色蒙版算法(CMA)来识别和量化肺气肿,从而通过伪彩色增强其可视化效果。我们研究了7例COPD患者和1名健康志愿者的21幅图像。 CMA根据Hounsfield单位的预定义范围将颜色应用于分割的肺部。 CMA自动计算在预定范围内的层析密度所占的相对面积,从而可以准确量化病变和正常的实质。为了验证在慢性阻塞性肺病患者肺气肿图像评估中纳入CMA的有效性,还需要进一步的工作。

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