[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 …

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 …

Micro-network-based deep convolutional neural network for human activity recognition from realistic and multi-view visual data

A Kushwaha, A Khare, O Prakash - Neural Computing and Applications, 2023 - Springer
In the recent past, deep convolutional neural network (DCNN) has been used in majority of
state-of-the-art methods due to its remarkable performance in number of computer vision …

Superpixelgridmasks data augmentation: Application to precision health and other real-world data

K Hammoudi, A Cabani, B Slika, H Benhabiles… - Journal of Healthcare …, 2022 - Springer
A novel approach of data augmentation based on irregular superpixel decomposition is
proposed. This approach called SuperpixelGridMasks permits to extend original image …

FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images

G Juez-Castillo, B Valencia-Vidal, LM Orrego… - Medical Image …, 2024 - Elsevier
Protozoan parasites are responsible for dramatic, neglected diseases. The automatic
determination of intracellular parasite burden from fluorescence microscopy images is a …

[HTML][HTML] Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging

CF Otesteanu, R Caldelari, V Heussler… - Computational and …, 2024 - Elsevier
Malaria, a significant global health challenge, is caused by Plasmodium parasites. The
Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study …

Deep learning-based cell detection and extraction in thin blood smears for malaria diagnosis

DK Ufuktepe, F Yang, YM Kassim, H Yu… - 2021 IEEE Applied …, 2021 - ieeexplore.ieee.org
Malaria is a major health threat caused by Plasmod-ium parasites that infect the red blood
cells. Two predominant types of Plasmodium parasites are Plasmodium vivax (P. vivax) and …

Diagnosing malaria with AI and image processing

MK Dath, N Nazir - … on Innovative Practices in Technology and …, 2023 - ieeexplore.ieee.org
This research seeks to investigate the possibility of using deep learning strategies in the
process of diagnosing malaria, a virus that affects billions of people all over the world …

Staining-Independent Malaria Parasite Detection and Life Stage Classification in Blood Smear Images.

T Xu, N Theera-Umpon… - … Sciences (2076-3417), 2024 - search.ebscohost.com
Malaria is a leading cause of morbidity and mortality in tropical and sub-tropical regions.
This research proposed a malaria diagnosis system based on the you only look once …

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 …