Giemsa-stained Blood Smear Images

Giemsa stain is a type of Romanowsky stain, and it is the most widely used method for staining blood smears for malaria diagnosis. It is a relatively simple and inexpensive procedure, and it is effective for staining all four species of malaria parasites that infect humans.

It is a mixture of eosin and methylene blue, and it stains the cytoplasm of malaria parasites blue and the nucleus red. This makes it possible to see the parasites under a microscope and identify the different species of malaria.

Datasets

• Yu et al., 2023 Image Dataset - It is a thick and thin, Giemsa-stained blood smear image dataset.

• de Souza Oliveira et al., 2022 Image Dataset - It is a thick blood smear, Giemsa-stained image dataset that contains 676 images.

• Arshad et al., 2022 Image Dataset - It is a thin blood smear, Giemsa-stained image dataset that contains 345 images.

• Manescu et al., 2020 Image Dataset - It is a thick, Giemsa-stained blood smear image dataset.

• MP-IDB: The Malaria Parasite Image Database for Image Processing and Analysis - It is a thin blood smear, Giemsa-stained image dataset. It contains Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax and Plasmodium malariae.

• National Institute of Health Plasmodium falciparum Dataset - It is a thin and thick, Giemsa-stained blood smear image dataset.

• National Institute of Health Plasmodium vivax Dataset - It is a thick, Giemsa-stained, blood smear image dataset.

• Taiwan Images for Malaria Eradication (TIME) - It is a thin, Giemsa-stained malaria image dataset.

• Aladago et al., 2019 Image Dataset - This is a thin, Giemsa-stained image dataset that consists of 403 images.

• Dantas Oliveira et al., 2018 Image Dataset - This is a thin, Giemsa-stained blood smear image and contains 50 images.

• Dave, 2018 Image Dataset - This is a thick, Giemsa-stained image dataset consisting of 87 images.

• Rosnelly et al., 2017 Image Dataset - It is a thin, Giemsa-stained image dataset consisting of 600 images. Plasmodium falciparum, vivax and malariae life stages are in the images.

• Cruz et al., 2016 Image Dataset - This is a thin, Giemsa-stained dataset with a total of 267 images. P. falciparum, P. vivax and P. malariae are present in the images.

• Preedanan et al., 2016 Image Dataset - This is a thin, Giemsa-stained dataset with 15 images.

• Abdul-Nasir et al., 2015 Image Dataset - This is a thin, Giemsa-stained dataset with 125 images.

• Nugroho et al., 2014 Image Dataset - This is a thin, Giemsa-stained blood smear image dataset. It contains 177 microphotographs.

• Linder et al., 2014 Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.

• Loh et al., 2020 Image Dataset - It is a Giemsa-stained blood smear image dataset

• National Reference Center Image Dataset - This is a thin, Giemsa-stained blood smear image dataset with 1250 images.

• SmartMalariaNet Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Sengar et al., 2022 Image Dataset - It is a thin, Giemsa-stained blood smear image

• Salamah et al., 2019 Image Dataset - This is a thick image dataset consisting of 30 images.

• Davidson et. al., 2021 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset with 108 images.

• Broad Bioimage Benchmark Collection - It is a thin, Giemsa-stained blood smear image dataset containing Plasmodium vivax.

• Yoon et. al., 2021 Image Dataset - It is a thick and thin, Giemsa-stained blood smear image dataset. It contains Plasmodium falciparum and vivax.

• Sunarko et al., 2017 Image Dataset - It is a thick and thin, Giemsa-stained blood smear image dataset.

• Zhong et al., 2023 Image Dataset - It is a thick, Giemsa-stained blood smear image dataset.

• Hartati et al., 2019 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset

• Tantisatirapong & Phothisonothai, 2018 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset

• Kudisthalert et al., 2020 Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.

• Vijayalakshmi & Rajesh, 2019 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Karimi et al., 2014 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Gh-Lab Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Hung et al., 2015 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Kanakasabapathy et al., 2021 Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.

• Shaka et al., 2020 Image Dataset - It is a thick, Giemsa-stained blood smear image dataset.

• Xiong et al., 2015 Image Dataset - It is a Giemsa-stained, blood smear image dataset.

• Malaria Research Centre, UNIMAS, Sarawak Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.

• Özbilge et al., 2024 Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.

• Muhammad et al., 2025 Image Dataset - It is a thin, Giemsa-stained blood smear image dataset.

• Adebayo et al., 2024 Image Dataset - It is a thick and thin, Giemsa-stained blood smear image dataset.

• Fundação Oswaldo Cruz (FIOCRUZ) Image Dataset - This is a thin, Giemsa-stained blood smear image dataset.