Automatic Counting Red Blood Cells in the Microscopic Images by EndPoints Method and Circular Hough Transform

被引:2
作者
Aslani, Amir Aslan [1 ]
Zolfaghari, Mohammad [2 ]
Sajedi, Hedieh [1 ]
机构
[1] Univ Tehran, Coll Sci, Sch Math Stat & Comp Sci, Dept Comp Sci, Tehran, Iran
[2] Univ Tehran, Dept Comp Sci, Kish Int Campus, Tehran, Iran
来源
PROCEEDINGS OF THE 2022 16TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INFORMATION MANAGEMENT AND COMMUNICATION (IMCOM 2022) | 2022年
关键词
RBCs; WBCs; Segmentation; Canny method; Marginal image; EndPoints set; CHT;
D O I
10.1109/IMCOM53663.2022.9721754
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many diseases such as anemia and leukemia are detected by counting Red Blood Cells (RBCs or erythrocytes). Generally, there are manual and automatic method for RBCs counting. In the manual method, RBCs counting is performed by a hematologist with the help of special medical equipment. The manual method is tedious, time-consuming and dependent on equipment and hematologist's expert and accuracy. The automatic method is fast, high accuracy and independent of equipment and hematologist. It is performed with the assistance of a microscopic image of the person's blood and a computer system. In this paper, a new method is presented for counting incomplete or cropped RBCs by Circular Hough Transform (CHT) and another method called EndPoints method which will be described in the following. Two parallel tasks are performed on the input image. In the first work, the input image is segmented using thresholding and erosion on the green channel. In the second work, the input image is converted to a grayscale image and edged by the Canny method. Then, the segmented image is subtracted from the edged image and remove White Blood Cells (WBCs or leucocytes) from it. After margin is added, by defining EndPoints set estimated continuation of RBCs will be added to the image. Finally, CHT is applied to the image and it will calculate the number of RBCs. Also, new counting error and counting accuracy metrics are defined for counting problem. The method is evaluated on the fifteen images of the ALL-LDB1 database and achieved 97.14 overall accuracy.
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页数:5
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