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University of Dayton

Series

2019

Computer Aided Detection

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Full-Text Articles in Engineering

Performance Analysis Of Machine Learning And Deep Learning Architectures For Malaria Detection On Cell Images, Barath Narayanan, Redha Ali, Russell C. Hardie Jan 2019

Performance Analysis Of Machine Learning And Deep Learning Architectures For Malaria Detection On Cell Images, Barath Narayanan, Redha Ali, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Plasmodium malaria is a parasitic protozoan that causes malaria in humans. Computer aided detection of Plasmodium is a research area attracting great interest. In this paper, we study the performance of various machine learning and deep learning approaches for the detection of Plasmodium on cell images from digital microscopy. We make use of a publicly available dataset composed of 27,558 cell images with equal instances of parasitized (contains Plasmodium) and uninfected (no Plasmodium) cells. We randomly split the dataset into groups of 80% and 20% for training and testing purposes, respectively. We apply color constancy and spatially resample all images …