Diagnosing Malaria Patients with <i>Plasmodium falciparum</i> and <i>vivax</i> Using Deep Learning for Thick Smear Images

Diagnosing Malaria Patients with <i>Plasmodium falciparum</i> and <i>vivax</i> Using Deep Learning for Thick Smear Images

We propose a new framework, PlasmodiumVF-Net, to analyze thick smear microscopy images for a malaria diagnosis on both image and patient-level. Our framework detects whether a patient is infected, and in case of a malarial infection, reports whether the patient is infected by <i>Plasmodium fal...

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Bibliographic Details
Main Authors:	Yasmin M. Kassim, Feng Yang, Hang Yu, Richard J. Maude, Stefan Jaeger
Format:	Article
Language:	English
Published:	MDPI AG 2021-10-01
Series:	Diagnostics
Subjects:	malaria computer-aided diagnosis biomedical image analysis deep learning ResNet50 Mask R-CNN
Online Access:	https://www.mdpi.com/2075-4418/11/11/1994

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