Malaria diagnosis: still a challenge in non-endemic countries

Voulgaridi, Ioanna; Koufakis, Theocharis; Ntava, Evdokia; Zisis, Nikolaos; Tsiakalou, Maria

doi:10.1016/j.bjid.2016.05.002

Cited by 2 publications

(2 citation statements)

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“…Every year about 3.2 billion people are at risk of global cases of malaria which is nearly half of the world's population. In 2015, WHO latest estimates repel that about 438000 death occurs for malaria infection (range 236,000-635,000) worldwide (Boes et al, 2016;Voulgaridi et al, 2016). As per the survey, maximum death cases of malaria occur in African region (90%), South-East Asia region (7%) and Eastern Mediterranean region (2%).…”

Section: Brief Historymentioning

confidence: 92%

Vision-based malaria parasite image analysis: a systematic review

Pattanaik

Swarnkar

2019

IJBRA

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Background: Malaria is one of the classic neglected serious diseases in many developing countries. The early stage of disease detection, accurate parasite count, detection of the aggressiveness of the disease, technical limitations, lack of expertise in malaria diagnosis and smart tools, lack of good quality healthcare services, funds so on are the challenges found during malaria diagnosis that requires a deeper analysis. Objectives: This paper aims to give a review of the automated diagnosis or visual inspection of malaria parasites using histology images of thin or thick blood film smears. Methods and Results: Various computer-aided diagnosis techniques are in use to solve tasks meticulously in a stratified description paradigm using non-linear transformation architectures. Conclusion: This work elaborates a comprehensive study of various computer vision diagnostic approaches already proposed in this field with a future direction for better quicker malaria identification.

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