Automatic Segmentation and Classification of Mycobacterium Tuberculosis with Conventional Light Microscopy
Refereed conference paper presented and published in conference proceedings


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摘要This paper realizes the automatic segmentation and classification of Mycobacterium tuberculosis with conventional light microscopy. First, the candidate bacillus objects are segmented by the marker-based watershed transform. The markers are obtained by an adaptive threshold segmentation based on the adaptive scale Gaussian filter. The scale of the Gaussian filter is determined according to the color model of the bacillus objects. Then the candidate objects are extracted integrally after region merging and contaminations elimination. Second, the shape features of the bacillus objects are characterized by the Hu moments, compactness, eccentricity, and roughness, which are used to classify the single, touching and non-bacillus objects. We evaluated the logistic regression, random forest, and intersection kernel support vector machines classifiers in classifying the bacillus objects respectively. Experimental results demonstrate that the proposed method yields to high robustness and accuracy. The logistic regression classifier performs best with an accuracy of 91.68%.
著者Xu C, Zhou DX, Zhai YP, Liu YH
會議名稱9th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Parallel Processing of Images and Optimization; and Medical Imaging Processing
會議開始日31.10.2015
會議完結日01.11.2015
會議地點Enshi
會議國家/地區中國
期刊名稱Proceedings of SPIE
出版年份2015
月份1
日期1
卷號9814
出版社SPIE-INT SOC OPTICAL ENGINEERING
電子國際標準書號978-1-5106-0055-3
國際標準期刊號0277-786X
語言英式英語
關鍵詞computer-aided diagnosis; Gaussian filter; Mycobacterium tuberculosis; watershed transform
Web of Science 學科類別Optics

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