Malaria Screener: a smartphone application for automated malaria screening

被引:24
作者
Yu, Hang [1 ]
Yang, Feng [1 ]
Rajaraman, Sivaramakrishnan [1 ]
Ersoy, Ilker [2 ]
Moallem, Golnaz [1 ,3 ]
Poostchi, Mahdieh [1 ]
Palaniappan, Kannappan [4 ]
Antani, Sameer [1 ]
Maude, Richard J. [5 ,6 ,7 ]
Jaeger, Stefan [1 ]
机构
[1] NIH, Lister Hill Natl Ctr Biomed Commun, Natl Lib Med, Bethesda, MD 20894 USA
[2] Univ Missouri, Inst Data Sci & Informat, Columbia, MO 65211 USA
[3] Texas Tech Univ, Elect & Comp Engn Dept, Lubbock, TX 79409 USA
[4] Univ Missouri Columbia, Elect Engn & Comp Sci Dept, Columbia, MO 65211 USA
[5] Mahidol Univ, Mahidol Oxford Trop Med Res Unit, Bangkok 10400, Thailand
[6] Univ Oxford, Nuffield Dept Med, Ctr Trop Med & Global Hlth, Oxford, England
[7] Harvard Univ, Harvard TH Chan Sch Publ Hlth, Boston, MA 02115 USA
基金
英国惠康基金; 美国国家卫生研究院;
关键词
Automated light microscopy; Smartphone application; Malaria; Machine learning; Convolutional neural network; PARASITE DETECTION; BLOOD;
D O I
10.1186/s12879-020-05453-1
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundLight microscopy is often used for malaria diagnosis in the field. However, it is time-consuming and quality of the results depends heavily on the skill of microscopists. Automating malaria light microscopy is a promising solution, but it still remains a challenge and an active area of research. Current tools are often expensive and involve sophisticated hardware components, which makes it hard to deploy them in resource-limited areas.ResultsWe designed an Android mobile application called Malaria Screener, which makes smartphones an affordable yet effective solution for automated malaria light microscopy. The mobile app utilizes high-resolution cameras and computing power of modern smartphones to screen both thin and thick blood smear images for P. falciparum parasites. Malaria Screener combines image acquisition, smear image analysis, and result visualization in its slide screening process, and is equipped with a database to provide easy access to the acquired data.ConclusionMalaria Screener makes the screening process faster, more consistent, and less dependent on human expertise. The app is modular, allowing other research groups to integrate their methods and models for image processing and machine learning, while acquiring and analyzing their data.
引用
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页数:8
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