Biomedical Engineering, Near East University, 99138 Nicosia TRNC Mersin 10, Turkey.
Computer Engineering, Near East University, 99138 Nicosia TRNC Mersin 10, Turkey.
Scanning. 2021 Dec 6;2021:5678117. doi: 10.1155/2021/5678117. eCollection 2021.
Manual counting and evaluation of red blood cells with the presence of malaria parasites is a tiresome, time-consuming process that can be altered by environmental conditions and human error. Many algorithms were presented to segment red blood cells for subsequent parasitemia evaluation by machine learning algorithms. However, the segmentation of overlapping red blood cells always has been a challenge. Marker-controlled watershed segmentation is one of the methods that was implemented to separate overlapping red blood cells. However, a high number of overlapped red blood cells were still an issue. We propose a novel approach to improve the segmentation efficiency of marker-controlled watershed segmentation. Local minimum histogram background segmentation with a selective hole filling algorithm was introduced to improve segmentation efficiency of marker-controlled watershed segmentation on a high number of overlapping red blood cells. The local minimum was selected on the smoothed histogram for background segmentation. The combination of selective filling, convex hull, and Hough circle detection algorithms was utilized for the intact segmentation of red blood cells. The markers were computed from the resulted mask, and finally, marker-controlled watershed segmentation was applied to separate overlapping red blood cells. As a result, the proposed algorithm achieved higher background segmentation accuracy compared to popular background segmentation algorithms, and the inclusion of corner details improved watershed segmentation efficiency.
手动计数和评估有疟原虫存在的红细胞是一项繁琐且耗时的工作，其过程易受环境条件和人为错误的影响。已经提出了许多算法来分割红细胞，以便随后通过机器学习算法评估寄生虫血症。然而，重叠红细胞的分割一直是一个挑战。标记控制分水岭分割是一种用于分离重叠红细胞的方法。然而，大量重叠的红细胞仍然是一个问题。我们提出了一种改进标记控制分水岭分割的分割效率的新方法。引入局部最小直方图背景分割和选择性空洞填充算法，以提高大量重叠红细胞的标记控制分水岭分割的分割效率。在平滑后的直方图上选择局部最小值以进行背景分割。选择填充、凸壳和霍夫圆检测算法的组合用于红细胞的完整分割。从得到的掩模中计算出标记，最后应用标记控制分水岭分割来分离重叠的红细胞。结果表明，与流行的背景分割算法相比，所提出的算法实现了更高的背景分割精度，并且角细节的包含提高了分水岭分割的效率。
