Controlled Access Datasets

This is a collection of controlled-access datasets as reported by the researchers. This collection contains both datasets with both thick and thin image datasets and those with thick and thin image datasets only.

• Aris et al., 2021 Image Dataset - This is a thick and thin image dataset. Plasmodium falciparum and vivax are the species of interest.

• Khan et al., 2017 Image Dataset - This is a thick and thin Leishman-stained blood smear image dataset. It has a total of 330 images.

• 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.

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

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

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

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

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

• Hung et al., 2017 Image Dataset - This is a thin blood smear image dataset containing 1,300 images.

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

• 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.

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

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

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

• Kanafiah et al., 2022 Image dataset - It is a thin blood smear image dataset that contains 150 images. Plasmodium knowlesi, _vivax _and falciparum are the species of interest.

• Aris et al., 2021 Image Dataset - This is a thick and thin image dataset. Plasmodium falciparum and vivax are the species of interest.

• Maity et al., 2020 Image Dataset - This is a thin blood smear image dataset. It has 210 images, with 90 images of P. falciparum and 120 images of P. vivax.

• Delas Peñas et al., 2018 Image Dataset - This is a thin blood smear image dataset consisting of 363 images. 142 images contain P. vivax while 221 images contain P. falciparum.

• Devi et al., 2018 Image Dataset - This is a thin, Leishman-stained blood smear image with a total of 400 images. P. falciparum and P. vivax are the species of interest.

• (mThinMPs) Image Database - The database has 566 images. It contains Plasmodium falciparum, ovale and malariae.

• 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.

• Das et al., 2015 Image Dataset - This is a thin Leishman-stained dataset with 750 images containing P. falciparum and P. vivax.

• Fu et al., 2023 Image Dataset - It has a total of 42,787 blood slice images that contains Plasmodium falciparum, vivax, ovale and malariae.

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

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

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

• Wang et al., 2023 Image Dataset - It is a thin, Wright 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

• Sampathila et al., 2018 Image Dataset - It is a thin, Leishman-stained blood smear image dataset.

• Nugroho et al., 2019 Image Dataset - This is a thin blood smear image dataset.

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

• Shi et al., 2020 Image Dataset - It is a 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.

• Adi et al., 2016 Image Dataset - It is a blood smear image dataset.

• BBLK Image Dataset - It is a blood smear image dataset containing P. falciparum, P. vivax, P. ovale and P. malariae.

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

• Krappe et al., 2017 Image Dataset - It is a thick, blood smear image dataset.

• PlasmoID Image Dataset - This is a thin, blood smear image dataset.

• Rahmanti et al., 2015 Image Dataset - It is a thick, blood smear image dataset.

• Sharma et al., 2022 Image Dataset - This is a thin, Leishman-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.

• Chamidah et al., 2024 Image Dataset - This is a blood smear image dataset.

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