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An algorithm for Giardia Lamblia detection in digital images acquired through an optical microscope

机译:一种通过光学显微镜获取的数字图像中Giardia Lamblia检测算法

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This work proposes an algorithm for the detection of the intestinal parasite Giardia Lamblia from digital images obtained through a digital camera and an optical microscope. Its purpose is to reduce the time of visual inspection analysis of the sample made by the specialist in laboratory. The proposed algorithm converts the acquired RGB images to the HSV colour space. First, the saturation component is filtered using a Gaussian filter, in order to reduce the noise and standardize the areas of interest. The filtered image is thresholdized using a fixed threshold value, in order to segment the objects of interest. Then, using a labelling algorithm, a filtering is performed by object size, in order to eliminate those that do not comply with the dimensions of the parasite. Therefore, the edges are highlighted by a Canny filter, to finally apply the Hough transform and detect the morphology of the object and its physical dimensions. With this information it will be possible to validate if the object satisfies the conditions of a Giardia Lamblia parasite. The proposed method achieved a specificity of 86% and a sensitivity of 67%, processing each image in an average time of less than 2 seconds. The results were obtained from a universe of 30 images.
机译:这项工作提出了一种从数字照相机和光学显微镜获得的数字图像检测肠道寄生虫Giardia落叶的算法。其目的是减少专家在实验室中的样本的视觉检查分析时间。该算法将所获取的RGB图像转换为HSV颜色空间。首先,使用高斯滤波器过滤饱和分量,以减少噪声并标准化感兴趣的区域。使用固定阈值阈值阈值,滤波过滤的图像,以便分段感兴趣的对象。然后,使用标签算法,通过对象大小进行滤波,以消除那些不符合寄生虫尺寸的那些。因此,通过罐式滤波器突出显示边缘,最终应用Hough变换并检测物体的形态及其物理尺寸。利用这些信息,可以验证对象是否满足Giardia Lamblia寄生虫的条件。所提出的方法实现了86%的特异性和67%的灵敏度,在少于2秒的平均时间处理每个图像。结果是从30个图像的宇宙中获得的。

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