Davidson et. al., 2021 Image Dataset
Article Title: Automated detection and staging of malaria parasites from cytological smears using convolutional neural networks
Article Link: ref
Description
It is a thin, Giemsa-stained blood smear image dataset.
Demography
- Parasite’s species: Plasmodium falciparum strains 3D7, NF54, DD2, and D10
Imaging Technique
- Magnification: 100×
- Number of Images: 108 images
Dataset Specifications
| Microscope Brand + Model | Strain | Number of Images |
|---|---|---|
| Olympus | Plasmodium falciparum 3D7 | 20 |
| Zeiss Axioskop 40 | Plasmodium falciparum NF54 | 66 |
| Leica DM750 | Plasmodium falciparum 3D7 | 65 |
| Nikon Ti2-E Inverted Microscope | Plasmodium falciparum NF54 | 84 |
| Olympus LC20 | Plasmodium falciparum 3D7, DD2, D10 | 48 |
| Olympus BX40 with INFINITY3-6UR camera | Plasmodium falciparum 3D7 | 127 |
Dataset Availability
| Status | Dataset Link | DOI |
|---|---|---|
| Publicly Available | Dataset | 10.1017/S2633903X21000015 |
Cite this Article
❗🛑 If you are using this resource, please cite:
Davidson MS, Andradi-Brown C, Yahiya S, Chmielewski J, O'Donnell AJ, Gurung P, Jeninga MD, Prommana P, Andrew DW, Petter M, Uthaipibull C, Boyle MJ, Ashdown GW, Dvorin JD, Reece SE, Wilson DW, Cunningham KA, Ando DM, Dimon M, Baum J. Automated detection and staging of malaria parasites from cytological smears using convolutional neural networks. Biol Imaging. 2021 Aug 2;1:e2. doi: 10.1017/S2633903X21000015. PMID: 35036920; PMCID: PMC8724263.