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Computer-Aided Diagnosis of Pathological Section for Eosinophilic Gastroenteritis

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嗜酸性粒细胞胃肠炎(EG)是一种以外周血嗜酸性粒细胞(EOS)增多为特征的胃肠道疾病,其主要诊断依据为消化道黏膜标本病理切片中嗜酸性粒细胞的数目是否超标。利用计算机图像分析算法对病理切片图像中的嗜酸性粒细胞进行识别并计数,旨在辅助病理医生人工计算EOS的数目,减少医生的工作量,提高工作效率。采用鲁棒性较强的分水岭算法作为识别EOS的核心算法,并通过距离变换和前后景标记的改进算法解决传统分水岭算法中的过分割问题,提高识别计数的准确性。采用改进分水岭算法对EG病理图像中的EOS进行识别计数,并将其与病理医生的金标准进行比对。改进分水岭算法的平均准确率为95.0%。与传统算法相比,改进算法准确率的相对标准方差由5.8%提高到2.2%,过分割率由13.4%降低为3.7%,算法的运行时间由40 s缩短为27 s左右。


Eosinophilic gastroenteritis (EG) is a gastrointestinal disease characterized by an increase in peripheral blood eosinophil (EOS). The main diagnosis of EG is based on whether the number of eosinophils in the pathological section of a digestive tract mucosa specimen exceeds the standard. In this study, a computer image analysis algorithm was used to identify and count eosinophils in pathological section images, with the aim to assist pathologists to manually calculate the number of EOS and reduce the workload and improve the work efficiency of doctors. A robust watershed algorithm was used as the core algorithm for identifying EOS, and the over-segmentation problem in the traditional watershed algorithm was solved using an improved distance transform algorithm and foreground and background markers. The accuracy of the watershed algorithm for recognition and counting was improved. The improved watershed algorithm was used to identify and count EOS, and its results were compared with a pathologist''s standard. The average accuracy of the algorithm is 95.0%. Compared with the traditional watershed algorithm, the relative standard deviation of the improved algorithm improved from 5.8% to 2.2%, the over-segmentation rate reduced from 13.4% to 3.7%, and the running time of the algorithm reduced from 40 s to about 27 s.

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万真真:河北大学电子信息工程学院, 河北 保定 071002
李春雪:河北大学电子信息工程学院, 河北 保定 071002
刘芳:保定市儿童医院病理科, 河北 保定 071000保定市儿童呼吸消化疾病临床研究重点实验室, 河北 保定 071000
张绍永:河北大学电子信息工程学院, 河北 保定 071002
韩帅:河北大学电子信息工程学院, 河北 保定 071002



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Wan Zhenzhen,Li Chunxue,Liu Fang,Zhang Shaoyong,Han Shuai. Computer-Aided Diagnosis of Pathological Section for Eosinophilic Gastroenteritis[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201701

万真真,李春雪,刘芳,张绍永,韩帅. 嗜酸性粒细胞胃肠炎病理切片的计算机辅助诊断[J]. 激光与光电子学进展, 2020, 57(20): 201701

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