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基于计算机的特发性肺纤维化定量计算机断层扫描图像分析:一篇综述。

Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review.

作者信息

Ohkubo Hirotsugu, Nakagawa Hiroaki, Niimi Akio

机构信息

Department of Respiratory Medicine, Allergy and Clinical Immunology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.

Division of Respiratory Medicine, Department of Internal Medicine, Shiga University of Medical Science, Shiga, Japan.

出版信息

Respir Investig. 2018 Jan;56(1):5-13. doi: 10.1016/j.resinv.2017.10.003. Epub 2017 Dec 7.

Abstract

Idiopathic pulmonary fibrosis (IPF) is the most common type of progressive idiopathic interstitial pneumonia in adults. Many computer-based image analysis methods of chest computed tomography (CT) used in patients with IPF include the mean CT value of the whole lungs, density histogram analysis, density mask technique, and texture classification methods. Most of these methods offer good assessment of pulmonary functions, disease progression, and mortality. Each method has merits that can be used in clinical practice. One of the texture classification methods is reported to be superior to visual CT scoring by radiologist for correlation with pulmonary function and prediction of mortality. In this mini review, we summarize the current literature on computer-based CT image analysis of IPF and discuss its limitations and several future directions.

摘要

特发性肺纤维化(IPF)是成人中最常见的进行性特发性间质性肺炎类型。许多用于IPF患者的基于计算机的胸部计算机断层扫描(CT)图像分析方法包括全肺的平均CT值、密度直方图分析、密度掩膜技术和纹理分类方法。这些方法大多能很好地评估肺功能、疾病进展和死亡率。每种方法都有可用于临床实践的优点。据报道,其中一种纹理分类方法在与肺功能的相关性和死亡率预测方面优于放射科医生的CT视觉评分。在这篇小型综述中,我们总结了目前关于IPF基于计算机的CT图像分析的文献,并讨论了其局限性和几个未来方向。

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