Efficient Malaria Parasite Detection From Diverse Images of Thick Blood Smears for Cross-Regional Model Accuracy

Efficient Malaria Parasite Detection From Diverse Images of Thick Blood Smears for Cross-Regional Model Accuracy

<italic>Goal</italic>: The purpose of this work is to improve malaria diagnosis efficiency by integrating smartphones with microscopes. This integration involves image acquisition and algorithmic detection of malaria parasites in various thick blood smear (TBS) datasets sourced from diff...

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Bibliographic Details
Main Authors: Yuming Zhong, Ying Dan, Yin Cai, Jiamin Lin, Xiaoyao Huang, Omnia Mahmoud, Eric S. Hald, Akshay Kumar, Qiang Fang, Seedahmed S. Mahmoud
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Computer-aided diagnosis
image segmentation
malaria parasites
microscope
neural networks
smartphones
Online Access:https://ieeexplore.ieee.org/document/10301747/

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