Menghitung Jumlah Sel Goblet Usus Ayam Secara Otomatis Dengan Metode Multilevel Thresholding

Dedi Sepriana, Kusworo Adi, Catur Adi Widodo
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Abstract

Goblet cell was an indicator the health of chicken intestine that was strongly influence of chicken productivity. So far, the determination of goblet cell was conducted by visual used of microscope. These methods required a long time and also the result was subjective value. The aim of this study was image processed for calculating the number of goblet cells in the chicken intestine and assessed the method applied performance. The material used was 30 images of broiler intestine preparations with AB-PAS staining. The research was carried out used multilevel thresholding and labeling methods for calculating the number of goblet cells in intestine of chicken. Chicken intestinal tissue that had been prepared with AB-PAS staining was acquired used a microscope equipped with a camera and connected to a PC. The result of the acquisition was an RGB scale image, so needed to be converted into an HSV scale image. Next, conducted the extraction process the hue component to convert the image to a gray scale. The gray scale image can be used in the process of identifying goblet cells using the multilevel thresholding method. Objects in the form of goblet cells that have been separated from other tissues were then repaired using morphological operations. The results of morphological operations were then calculated using the labeling method. The results showed that the method applied was successful in automatically calculated the number of goblet cells. The results of calculations using the multilevel thresholding and labeling method had accuracy rate of 90% compared with the results of calculated of visually directly by analyst.
用多级通口服方法自动计算鸡内脏摄入量
杯状细胞是鸡肠道健康状况的一个指标,对鸡的生产能力有重要影响。迄今为止,杯状细胞的测定都是用显微镜目视法进行的。这些方法耗时较长,结果具有主观价值。本研究采用图像处理方法计算鸡肠道杯状细胞的数量,并对该方法的应用性能进行了评价。所用材料为30张经AB-PAS染色的肉鸡肠制剂图像。采用多层次阈值法和标记法对鸡肠道杯状细胞数量进行了研究。用带有摄像头的显微镜与PC相连,获取经AB-PAS染色制备好的鸡肠组织。采集的结果是RGB尺度的图像,因此需要转换为HSV尺度的图像。接下来,对色相分量进行提取处理,将图像转换为灰度。灰度图像可用于多级阈值法对杯状细胞进行识别。从其他组织中分离出来的杯状细胞形式的物体,然后使用形态学操作进行修复。然后用标记法计算形态学操作的结果。结果表明,该方法能够成功地实现杯状细胞数量的自动计算。与分析人员直接目测计算结果相比,采用多层阈值标记法计算的结果准确率达到90%。
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