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Automated Extraction of the Intestinal Parasite in the Microscopic Images Using Active Contours and the Hough Transform

机译:使用活性轮廓和霍夫变换自动提取微观图像中的肠道寄生虫

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摘要

Parasitical diseases are among the first cause of hospitalization and mortality. The diagnostics of intestinal parasitical diseases is based on stools specimens test through the microscopic image. The manual evaluation of microscopic images is time consuming and depends on the human expert. Digital images are extensively used in medicine for diagnostic and also for survey guidance. We present in this work a method of parasite extraction from microscopic images. The extraction scheme has four main steps: The first step is the edge detection using the multi-scale wavelet transform. The second step uses edges to locate the region of interest on the image by looking for the round or approximately round objects through the Hough transform. The circles detected by the Hough transform are used as the initial contour for the active contour. The third step applied an active contour model to locate the contour of the parasite. The last step uses this contour to extract the parasite through the logic operation with the original image and the mask corresponding to the interior of the contour. Experimental results show that the proposed scheme is very efficient for the extraction of parasite from the stools images. It has accurate segmentation ability despite of the poor quality or complex background of microscopic stools images.
机译:氏乳病是第一次住院和死亡的原因。肠癌疾病的诊断基于通过显微图像测试的粪便标本试验。微观图像的手动评估是耗时,取决于人类专家。数字图像广泛用于医学中的诊断和调查指导。我们在这项工作中存在一种寄生虫从微观图像提取方法。提取方案有四个主步骤:第一步是使用多尺度小波变换的边缘检测。第二步使用边缘通过Hough变换寻找圆形或大致圆对象来定位图像上的感兴趣区域。由Hough变换检测的圆圈用作活动轮廓的初始轮廓。第三步施加了活性轮廓模型以定位寄生虫的轮廓。最后一步使用该轮廓通过使用原始图像的逻辑操作和对应于轮廓内部的掩模来提取寄生虫。实验结果表明,该方案对从粪便图像提取寄生虫的效率非常有效。尽管微观粪便图像的质量差或复杂的背景,但它具有精确的分割能力。

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