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NOT Open Access | Point-of-care tests for malaria: speeding up the diagnostics at the bedside and challenges in malaria cases detection

November 4, 2020 - 15:54 -- NOT Open Access
Rei Yan SL, Wakasuqui F, Wrenger C
Diagn Microbiol Infect Dis. 2020 Nov;98(3):115122

Malaria remains as one of the major public health problems worldwide. About 228 million cases occurred in 2018 only, with Africa bearing about 93% of the cases. Asymptomatic population carrying the various forms of the parasite Plasmodium in endemic areas plays an important role in the spread of the disease. To tackle this battle, more sensitive and precise detection kits for malaria are crucial to better control the number of new malaria cases.

Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears

November 3, 2020 - 15:25 -- Open Access
Kassim YM, Palaniappan K, Yang F, Poostchi M, Palaniappan N, Maude RJ, Antani S, Jaeger S
IEEE J Biomed Health Inform. 2020 Oct 29;PP

Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy and reproducibility of repetitive tasks like manual segmentation and annotation. We propose a novel pipeline for red blood cell detection and counting in thin blood smear microscopy images, named RBCNet, using a dual deep learning architecture. RBCNet consists of a U-Net first stage for cell-cluster segmentation, followed by a second stage Faster R-CNN for detecting small cell objects within clusters, identified as connected components from the U-Net stage.

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