Comput Math Methods Med - Automatic detection and quantification of WBCs and RBCs using iterative structured circle detection algorithm.

Tópicos

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Resumo

Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.

Resumo Limpo

segment count blood cell consid import step help extract featur diagnos specif diseas like malaria leukemia manual count white blood cell wbcs red blood cell rbcs microscop imag extrem tedious time consum inaccur process automat analysi will allow hematologist expert perform faster accur propos method use iter structur circl detect algorithm segment count wbcs rbcs separ wbcs rbcs achiev threshold specif preprocess step develop cell type count perform imag use propos method base modifi circl detect automat count cell sever modif made basic rcd algorithm solv initi problem detect irregular circl cell select optim circl candid circl determin number iter fulli dynam way enhanc algorithm detect run time valid method use determin segment accuraci quantit analysi includ precis recal fmeasur test averag accuraci propos method rbcs wbcs

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