A Review of Automatic Malaria Parasites Detection and Segmentation in Microscopic Images
A Review of Automatic Malaria Parasites Detection and Segmentation in Microscopic Images
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DOI：
10.2174/221135251401160302121107
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发表时间：
2016-01-01
影响因子：
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通讯作者：
Cardoso, Jaime S.
中科院分区：
文献类型：
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作者：
Rosado, Luis;Correia da Costa, Jose M.;Cardoso, Jaime S.
背景资料：在许多发展中国家，疟疾是导致死亡和疾病的主要原因，其中幼儿和孕妇是最受影响的群体。2012年，估计有2.07亿例疟疾病例，造成约62.7万例疟疾死亡。大约80%的疟疾病例发生在非洲，那里缺乏疟疾诊断的机会主要是由于缺乏专业知识，设备短缺是次要因素。由于缺乏疟疾诊断的专门知识，往往导致假阳性增加，因为处方药物仅根据症状。因此，迫切需要新的工具，可以促进疟疾的快速，简便的诊断，特别是在有限的地区获得高质量的healthcare services.Methods：各种图像处理和分析方法已经提出的文献上的血涂片显微图像中的疟原虫的检测和分割进行了收集和审查。这及时审查的目的是支持开发低成本的工具，可以促进快速，方便地诊断疟疾，特别是在有限的地区获得优质的医疗服务的兴趣日益增加。结果：疟疾寄生虫检测和分割技术在显微镜图像，在一般情况下，仍然需要改进和进一步测试。在这项工作中审查的大多数方法都是用有限数量的图像进行测试的，需要用更大的数据集进行更多的研究，以评估所提出的方法。尽管在过去几年中报告了有希望的结果，但文献中发现的用于疟疾诊断的绝大多数计算机辅助方法都是基于在控制良好的条件下并使用适当的显微镜设备获得的图像。然而，人们应该考虑到，80%的疟疾病例发生在非洲，这种类型的设备是稀缺的，甚至不存在的，在共同的healthcare facilities.Conclusion：这项工作收集和审查各种图像处理和分析方法已经提出的文献上的血涂片显微图像中的疟原虫的检测和分割。这一及时审查的目的是支持对开发用于发展中国家农村地区的图像处理系统日益增长的兴趣，这可能是疟疾计算机辅助诊断的下一个未来趋势。
Background: Malaria is a leading cause of death and disease in many developing countries, where young children and pregnant women are the most affected groups. In 2012, there were an estimated 207 million cases of malaria, which caused approximately 627 000 malaria deaths. Around 80% of malaria cases occur in Africa, where the lack of access to malaria diagnosis is largely due to a shortage of expertise, being the shortage of equipment the secondary factor. This lack of expertise for malaria diagnosis frequently results on the increase of false positives, since prescription of medication is based only on symptoms. Thus, there is an urgent need of new tools that can facilitate the rapid and easy diagnosis of malaria, especially in areas with limited access to quality healthcare services.Methods: Various image processing and analysis approaches already proposed on the literature for the detection and segmentation of malaria parasites in blood smear microscopic images were collected and reviewed. This timely review aims to support the increasing interest in the development of low cost tools that can facilitate the rapid and easy diagnosis of malaria, especially in areas with limited access to quality healthcare services.Results: Malaria parasites detection and segmentation techniques in microscopic images are, in general, still in need of improvement and further testing. Most of the methodologies reviewed in this work were tested with a limited number of images, and more studies with significantly larger datasets for the evaluation of the proposed approaches are needed. Despite promising results reported during the past years, the great majority of the computer-aided methods found on the literature for malaria diagnosis are based on images acquired under well controlled conditions and with proper microscopic equipment. However, one should take into account that 80% of malaria cases occur in Africa, where this type of equipment is scarce or even nonexistent in common healthcare facilities.Conclusion: This work collects and reviews various image processing and analysis approaches already proposed on the literature for the detection and segmentation of malaria parasites in blood smear microscopic images. This timely review aims to support the increasing interest in the development of image processing-based systems to be used in rural areas of developing countries, which might be the next future trend in malaria computer-aided diagnosis.