Image enhancement and segmentation using dark stretching technique for Plasmodium Falciparum for thick blood smear

Color Constancy Analysis Approach for Color Standardization on Malaria Thick and Thin Blood Smear Images

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Automatic System for Plasmodium Species Identification from Microscopic Images of Blood-Smear Samples

Performance Evaluation of Filters for Enhancement of Images in Different Application Areas

Image enhancement and segmentation using dark stretching technique for Plasmodium Falciparum for thick blood smear

Image analysis and machine learning for detecting malaria. - Abstract - Europe PMC

AIDMAN: An AI-based object detection system for malaria diagnosis from smartphone thin-blood-smear images - ScienceDirect

PDF] Enhancement of low quality thick blood smear microscopic images of malaria patients using contrast and edge corrections

PDF] Performance Evaluation of Filters for Enhancement of Images in Different Application Areas

Modified Global and Modified Linear Contrast Stretching Algorithms: New Colour Contrast Enhancement Techniques for Microscopic Analysis of Malaria Slide Images

PDF] Performance Evaluation of Filters for Enhancement of Images in Different Application Areas

Recent advances on big data analysis for malaria prediction and various diagnosis methodologies - ScienceDirect

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks