Vision-based malaria parasite image analysis: a systematic review. (2019)

• Record Type: Journal Article
• Authors: Pattanaik, Priyadarshini Adyasha; Swarnkar, Tripti
• Is Part Of: International journal of bioinformatics research and applications. Volume 15:Number 1(2019)
• Page Start: 1
• Page End: 32
• Publication Date: 2019
• Subjects: malaria parasites -- microscopy analysis -- computer vision diagnosis -- deep learning; Bioinformatics -- Periodicals; 570.285
• Languages: English
• ISSNs: 1744-5485

Abstract

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.