Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer
Parasitic organisms pose a major global health threat, mainly in regions that lack advanced
medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives …
medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives …
iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope
Introduction Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa,
with 247 million cases reported worldwide in 2021 according to the World Health …
with 247 million cases reported worldwide in 2021 according to the World Health …
Convolutional neural networks to automate the screening of malaria in low-resource countries
OS Zhao, N Kolluri, A Anand, N Chu, R Bhavaraju… - PeerJ, 2020 - peerj.com
Malaria is an infectious disease caused by Plasmodium parasites, transmitted through
mosquito bites. Symptoms include fever, headache, and vomiting, and in severe cases …
mosquito bites. Symptoms include fever, headache, and vomiting, and in severe cases …
Leishmaniasis parasite segmentation and classification using deep learning
Leishmaniasis is considered a neglected disease that causes thousands of deaths annually
in some tropical and subtropical countries. There are various techniques to diagnose …
in some tropical and subtropical countries. There are various techniques to diagnose …
Malaria classification using convolutional neural network: a review
The Convolutional Neural Networks (CNNs) have been used to classify malaria parasites
from blood smear images automatically and successfully gave a good result, thus enabling …
from blood smear images automatically and successfully gave a good result, thus enabling …
Parasitologist-level classification of apicomplexan parasites and host cell with deep cycle transfer learning (DCTL)
S Li, Q Yang, H Jiang, JA Cortés-Vecino… - …, 2020 - academic.oup.com
Abstract Motivation Apicomplexan parasites, including Toxoplasma, Plasmodium and
Babesia, are important pathogens that affect billions of humans and animals worldwide …
Babesia, are important pathogens that affect billions of humans and animals worldwide …
[HTML][HTML] Enhancing medical image analysis with unsupervised domain adaptation approach across microscopes and magnifications
In the domain of medical image analysis, deep learning models are heralding a revolution,
especially in detecting complex and nuanced features characteristic of diseases like tumors …
especially in detecting complex and nuanced features characteristic of diseases like tumors …
A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic images
Malaria is an infectious disease caused by Plasmodium parasites and is potentially human
life-threatening. Children under 5 years old are the most vulnerable group with …
life-threatening. Children under 5 years old are the most vulnerable group with …
[PDF][PDF] Malaria parasite detection using deep learning methods
K Chakradeo, M Delves, S Titarenko - International Journal of …, 2021 - researchgate.net
Malaria is a serious disease which affects hundreds of millions of people around the world,
each year. If not treated in time, it can be fatal. Despite recent developments in malaria …
each year. If not treated in time, it can be fatal. Despite recent developments in malaria …
Malaria parasites detection and identification using object detectors based on deep neural networks: a wide comparative analysis
M Rocha, M Claro, L Neto, K Aires… - Computer Methods in …, 2023 - Taylor & Francis
Malaria is an infectious disease transmitted by the bite of the female Anopheles mosquito,
infected by Plasmodium spp. Early diagnosis and prompt and effective treatment are needed …
infected by Plasmodium spp. Early diagnosis and prompt and effective treatment are needed …