Malaria Thick Blood Smears

We photographed Giemsa-stained thick blood smear slides from 150 P. falciparum infected patients at Chittagong Medical College Hospital, Bangladesh, using a smartphone camera for the different microscopic field of views. Images are captured with 100x magnification in RGB color space with a 3024×4032 pixel resolution. An expert slide reader manually annotated each image at the Mahidol-Oxford Tropical Medicine Research Unit (MORU), Bangkok, Thailand. We de-identified all images andtheir annotations, and archived them at the National Library of Medicine (IRB#12972). Reference:We request that publications resulting from the use of this data attribute the source (National Library of Medicine, National Institutes of Health, Bethesda, MD, USA) and cite the following publication, which has used the data for parasite detection and classification:Feng Yang, Mahdieh Poostchi, Hang Yu, Zhou Zhou, Kamolrat Silamut, Jian Yu, Richard J Maude, Stefan Jaeger, Sameer Antani. Deep Learning for Smartphone-based Malaria Parasite Detection in Thick Blood Smears. IEEE J Biomed Health Inform. 2019 Sep 23. doi: 10.1109/JBHI.2019.2939121.