Deep learning for medical image processing: Overview, challenges and the future
MI Razzak, S Naz, A Zaib - … in BioApps: Automation of decision making, 2018 - Springer
The health care sector is totally different from any other industry. It is a high priority sector
and consumers expect the highest level of care and services regardless of cost. The health …
and consumers expect the highest level of care and services regardless of cost. The health …
[HTML][HTML] Image analysis and machine learning for detecting malaria
Malaria remains a major burden on global health, with roughly 200 million cases worldwide
and more than 400,000 deaths per year. Besides biomedical research and political efforts …
and more than 400,000 deaths per year. Besides biomedical research and political efforts …
[HTML][HTML] Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images
Malaria is a blood disease caused by the Plasmodium parasites transmitted through the bite
of female Anopheles mosquito. Microscopists commonly examine thick and thin blood …
of female Anopheles mosquito. Microscopists commonly examine thick and thin blood …
Machine learning and applications in microbiology
To understand the intricacies of microorganisms at the molecular level requires making
sense of copious volumes of data such that it may now be humanly impossible to detect …
sense of copious volumes of data such that it may now be humanly impossible to detect …
Performance analysis of deep learning algorithms in diagnosis of malaria disease
Malaria is predominant in many subtropical nations with little health-monitoring
infrastructure. To forecast malaria and condense the disease's impact on the population …
infrastructure. To forecast malaria and condense the disease's impact on the population …
Comparison of traditional image processing and deep learning approaches for classification of white blood cells in peripheral blood smear images
Automated classification and morphological analysis of white blood cells has been
addressed since last four decades, but there is no optimal method which can be used as …
addressed since last four decades, but there is no optimal method which can be used as …
Deep learning based automatic malaria parasite detection from blood smear and its smartphone based application
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is
detected by trained microscopists who analyze microscopic blood smear images. Modern …
detected by trained microscopists who analyze microscopic blood smear images. Modern …
Deep learning approach to detect malaria from microscopic images
A Vijayalakshmi - Multimedia Tools and Applications, 2020 - Springer
Malaria is an infectious disease which is caused by plasmodium parasite. Several image
processing and machine learning based techniques have been employed to diagnose …
processing and machine learning based techniques have been employed to diagnose …
Automatic white blood cell classification using pre-trained deep learning models: Resnet and inception
This works gives an account of evaluation of white blood cell differential counts via computer
aided diagnosis (CAD) system and hematology rules. Leukocytes, also called white blood …
aided diagnosis (CAD) system and hematology rules. Leukocytes, also called white blood …
Deep malaria parasite detection in thin blood smear microscopic images
Malaria is a disease activated by a type of microscopic parasite transmitted from infected
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …