This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.
[摘要] 本文综述了计算机视觉和图像分析技术应用于疟原虫薄血膜涂片显微图像自动检测的研究进展。在介绍自动 检测技术背景和意义的基础上, 首先对现有自动检测技术进行总结, 将其分为图像获取、前处理、形态学分析、图像分割、疟原虫计数与分类等步骤; 然后详细综述了各步骤的原理和现有实现方法; 最后提出了自动检测技术的推广应用及厚血 膜的自动检测等有待研究的问题, 为后续研究疟原虫图像的自动显微诊断提供了新思路。.
Keywords: Automatic detection; Image processing; Malaria parasite; Microscopic diagnosis; Morphological analysis; Thin blood film.