[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] An overview of organs-on-chips based on deep learning
Microfluidic-based organs-on-chips (OoCs) are a rapidly developing technology in
biomedical and chemical research and have emerged as one of the most advanced and …
biomedical and chemical research and have emerged as one of the most advanced and …
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 …
Automated image processing method for the diagnosis and classification of malaria on thin blood smears
NE Ross, CJ Pritchard, DM Rubin, AG Duse - Medical and Biological …, 2006 - Springer
Malaria is a serious global health problem, and rapid, accurate diagnosis is required to
control the disease. An image processing algorithm to automate the diagnosis of malaria on …
control the disease. An image processing algorithm to automate the diagnosis of malaria on …
Parasite detection and identification for automated thin blood film malaria diagnosis
This paper investigates automated detection and identification of malaria parasites in
images of Giemsa-stained thin blood film specimens. The Giemsa stain highlights not only …
images of Giemsa-stained thin blood film specimens. The Giemsa stain highlights not only …
[HTML][HTML] A semi-automatic method for quantification and classification of erythrocytes infected with malaria parasites in microscopic images
Visual quantification of parasitemia in thin blood films is a very tedious, subjective and time-
consuming task. This study presents an original method for quantification and classification …
consuming task. This study presents an original method for quantification and classification …
Automated Detection of P. falciparum Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells
Malaria detection through microscopic examination of stained blood smears is a diagnostic
challenge that heavily relies on the expertise of trained microscopists. This paper presents …
challenge that heavily relies on the expertise of trained microscopists. This paper presents …
Computer vision for microscopy diagnosis of malaria
This paper reviews computer vision and image analysis studies aiming at automated
diagnosis or screening of malaria infection in microscope images of thin blood film smears …
diagnosis or screening of malaria infection in microscope images of thin blood film smears …
Splitting touching cells based on concave points and ellipse fitting
X Bai, C Sun, F Zhou - Pattern recognition, 2009 - Elsevier
A new touching cells splitting algorithm based on concave points and ellipse fitting is
proposed in this paper. The algorithm includes two parts: contour pre-processing and ellipse …
proposed in this paper. The algorithm includes two parts: contour pre-processing and ellipse …
Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review
N KT, K Prasad, BMK Singh - Medical & biological engineering & …, 2022 - Springer
Anemia is a blood disorder which is caused due to inadequate red blood cells and
hemoglobin concentration. It occurs in all phases of life cycle but is more dominant in …
hemoglobin concentration. It occurs in all phases of life cycle but is more dominant in …