An efficient deep learning approach to automatic glaucoma detection using optic disc and optic cup localization

M Nawaz, T Nazir, A Javed, U Tariq, HS Yong… - Sensors, 2022 - mdpi.com
Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and
caused complete sightlessness at its progressed stage. Whereas timely glaucoma screening …

[HTML][HTML] Computer-Aided Diagnosis Systems for Automatic Malaria Parasite Detection and Classification: A Systematic Review

F Grignaffini, P Simeoni, A Alisi, F Frezza - Electronics, 2024 - mdpi.com
Malaria is a disease that affects millions of people worldwide with a consistent mortality rate.
The light microscope examination is the gold standard for detecting infection by malaria …

Parasitic egg recognition using convolution and attention network

N AlDahoul, HA Karim, MA Momo, FIF Escobar… - Scientific Reports, 2023 - nature.com
Intestinal parasitic infections (IPIs) caused by protozoan and helminth parasites are among
the most common infections in humans in low-and-middle-income countries. IPIs affect not …

Machine and deep learning methods in identifying malaria through microscopic blood smear: A systematic review

D Sukumarran, K Hasikin, ASM Khairuddin… - … Applications of Artificial …, 2024 - Elsevier
Despite the persistency of World Health Organization to eliminate malaria since 1987,
malaria disease continues to pose a significant threat to global health. As the severity of …

A lightweight deep learning architecture for malaria parasite-type classification and life cycle stage detection

HAH Chaudhry, MS Farid, A Fiandrotti… - Neural Computing and …, 2024 - Springer
Malaria is an endemic in various tropical countries. The gold standard for disease detection
is to examine the blood smears of patients by an expert medical professional to detect …

An optimized features selection approach based on Manta Ray Foraging Optimization (MRFO) method for parasite malaria classification

J Amin, M Sharif, GA Mallah… - Frontiers in Public Health, 2022 - frontiersin.org
Malaria is a serious and lethal disease that has been reported by the World Health
Organization (WHO), with an estimated 219 million new cases and 435,000 deaths globally …

Classifying parasitized and uninfected malaria red blood cells using convolutional-recurrent neural networks

AA Alonso-Ramírez, CH García-Capulín… - IEEE …, 2022 - ieeexplore.ieee.org
This work aims to classify malaria infected red blood cells from those uninfected using two
deep learning approaches. Plasmodium parasite transmitted by a female anopheles's …

HSV-Net: a custom cnn for malaria detection with enhanced color representation

G Hcini, I Jdey, H Ltifi - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Malaria disease should be considered and handled as a potential restorative catastrophe.
One of the most challenging tasks in the field of microscopy image processing is due to …

[PDF][PDF] RESEARCH ARTICLE An automated malaria cells detection from thin blood smear images using deep learning

D Sukumarran, K Hasikin, AS Mohd Khairuddin… - Tropical …, 2023 - msptm.org
Timely and rapid diagnosis is crucial for faster and proper malaria treatment planning.
Microscopic examination is the gold standard for malaria diagnosis, where hundreds of …

Classification of cells infected with the malaria parasite with resnet architectures

İ Akgül, V Kaya - Journal of Scientific Reports-A, 2022 - dergipark.org.tr
Malaria is a disease that causes a parasite called plasmodium to be transmitted to humans
as a result of the bite of female anopheles' mosquitoes. Malaria is detected by examining the …