基于Shannon熵的白细胞图像分割研究

N. M. Raja, S. Arunmozhi, Hong Lin, N. Dey, V. Rajinikanth
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引用次数: 14

摘要

近年来,研究人员提出了相当多的方法,通过检查使用显微镜记录的外周血细胞(PBC)的数字图像来评估传染病。在本章中,提出了一种半自动化的方法,将香农熵(SE)阈值和基于drls的分割过程相结合,从数字PBC图像中提取染色血细胞。本文实现了基于布谷鸟搜索(CS)和基于se的预处理和基于drls的后处理程序的两步实践来检测PBC图像。在实验中,PBC图像采用数据库白细胞图像进行分割和分类(LISC)。通过考虑RGB尺度和灰度版本的PBC图像来实现该方法,并通过计算提取的染色血细胞与真实图像的图像相似度和统计度量来验证该方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Segmentation of Leukocyte Image With Shannon's Entropy
In recent years, a considerable number of approaches have been proposed by the researchers to evaluate infectious diseases by examining the digital images of peripheral blood cell (PBC) recorded using microscopes. In this chapter, a semi-automated approach is proposed by integrating the Shannon's entropy (SE) thresholding and DRLS-based segmentation procedure to extract the stained blood cell from digital PBC pictures. This work implements a two-step practice with cuckoo search (CS) and SE-based pre-processing and DRLS-based post-processing procedure to examine the PBC pictures. During the experimentation, the PBC pictures are adopted from the database leukocyte images for segmentation and classification (LISC). The proposed approach is implemented by considering the RGB scale and gray scale version of the PBC pictures, and the performance of the proposed approach is confirmed by computing the picture similarity and statistical measures computed with the extracted stained blood cell with the ground truth image.
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