Automatic identification of tuberculosis mycobacterium

Introduction According to the Global TB control report of 2013, “Tuberculosis (TB) remains a major global health problem. In 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease. Two main sputum smear microscopy techniques are used for TB diagnosis: Fluorescence microscopy and conventional microscopy. Fluorescence microscopy is a more expensive diagnostic method because of the high costs of the microscopy unit and its maintenance. Therefore, conventional microscopy is more appropriate for use in developing countries. Methods This paper presents a new method for detecting tuberculosis bacillus in conventional sputum smear microscopy. The method consists of two main steps, bacillus segmentation and post-processing. In the first step, the scalar selection technique was used to select input variables for the segmentation classifiers from four color spaces. Thirty features were used, including the subtractions of the color components of different color spaces. In the post-processing step, three filters were used to separate bacilli from artifact: a size filter, a geometric filter and a Rule-based filter that uses the components of the RGB color space. Results In bacillus identification, an overall sensitivity of 96.80% and an error rate of 3.38% were obtained. An image database with 120-sputum-smear microscopy slices of 12 patients with objects marked as bacillus, agglomerated bacillus and artifact was generated and is now available online. Conclusions The best results were obtained with a support vector machine in bacillus segmentation associated with the application of the three post-processing filters.引言 根据2013年《全球结核病控制报告》显示，“结核病（TB）仍是全球性重大公共卫生问题。2012年，全球预估有860万人新发结核病，130万人因该病死亡。结核病诊断主要采用两种痰涂片显微镜检查技术：荧光显微镜法与常规显微镜法。荧光显微镜法因显微镜设备及其维护成本高昂，属于成本较高的诊断手段，因此常规显微镜法更适用于发展中国家。 方法 本文提出一种用于常规痰涂片显微镜检查中结核分枝杆菌检测的新方法。该方法包含两个核心步骤：杆菌分割与后处理。第一步采用标量选择技术，从4种色彩空间中选取用于分割分类器的输入变量，共提取30项特征，其中包含不同色彩空间的色彩分量差值。在后处理步骤中，采用三种滤波器实现杆菌与伪影的区分：尺寸滤波器、几何滤波器，以及基于RGB色彩空间分量的规则型滤波器。 结果 在杆菌识别任务中，本方法的整体识别灵敏度达96.80%，错误率为3.38%。本研究构建了一套图像数据库，包含12例患者的120张痰涂片显微镜切片，其中标注了杆菌、聚集杆菌与伪影三类目标，该数据库现已可在线获取。 结论 采用支持向量机进行杆菌分割，并结合三种后处理滤波器，可取得最优实验结果。