Automatic Detection of Tuberculosis in Chest Radiographs Using a Combination of Textural, Focal, and Shape Abnormality Analysis
Automatic Detection of Tuberculosis in Chest Radiographs Using a Combination of Textural, Focal, and Shape Abnormality Analysis
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DOI：
10.1109/tmi.2015.2405761
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发表时间：
2015-12-01
影响因子：
10.6
通讯作者：
van Ginneken, Bram
中科院分区：
文献类型：
--
作者：
Hogeweg, Laurens;Sanchez, Clara I.;van Ginneken, Bram
结核病是一种世界范围内死亡率和发病率都很高的常见病。胸片上检测结核病的自动系统(CXR)可以提高肺结核诊断算法的效率。不同人群的结核病在CXR上的不同表现需要一个能够适应不同类型异常的系统。开发了一种计算机辅助检测(CAD)系统，它将检测纹理、形状和局灶性异常的几个监督子系统合并为一个TB评分。开发了一个通用框架来组合任意数量的子分数：将子分数归一化，收集在特征向量中，然后使用监督分类器将其合并为一个组合分数。该方法在两个数据库上进行了评估，这两个数据库都由200个数字CXR组成，分别来自：(A)西方高危人群筛查，(B)非洲结核病嫌疑人筛查。将这些子评分和综合评分与(1)外部非放射学参考和(2)由人类专家确定的放射学参考进行比较。使用接收器操作员特征(ROC)分析来测量性能。不同的分项分数在两个数据库中表现最好。除数据库B中的外部参照外，合并的TB评分优于单独的分项评分。独立观察者的评分略高于合并的TB评分。与外部参照相比，在两个数据库中，合并的结核病评分和独立观察员之间的表现差异并不显著。受监督的组合以计算总的结核病分数，允许CAD系统根据不同的设置或不同的操作要求进行必要的调整。
Tuberculosis (TB) is a common disease with high mortality and morbidity rates worldwide. Automatic systems to detect TB on chest radiographs (CXRs) can improve the efficiency of diagnostic algorithms for pulmonary TB. The diverse manifestation of TB on CXRs from different populations requires a system that can be adapted to deal with different types of abnormalities. A computer aided detection (CAD) system was developed which combines several subscores of supervised subsystems detecting textural, shape, and focal abnormalities into one TB score. A general framework was developed to combine an arbitrary number of subscores: subscores were normalized, collected in a feature vector and then combined using a supervised classifier into one combined score. The method was evaluated on two databases, both consisting of 200 digital CXRs, from: (A) Western high-risk group screening, (B) TB suspect screening in Africa. The subscores and combined score were compared to (1) an external, non-radiological, reference and (2) a radiological reference determined by a human expert. Performance was measured using Receiver Operator Characteristic (ROC) analysis. Different subscores performed best in the two databases. The combined TB score performed better than the individual subscores, except for the external reference in database B. The performances of the independent observer were slightly higher than the combined TB score. Compared to the external reference, differences in performance between the combined TB score and the independent observer were not significant in both databases. Supervised combination to compute an overall TB score allows for a necessary adaptation of the CAD system to different settings or different operational requirements.