Kudisthalert et al., 2020 Image Dataset
Article Title: Counting and Classification of Malarial Parasite From Giemsa-Stained Thin Film Images
Article Link: ref
Description
This is a thin, Giemsa-stained blood smear image dataset
Demography
- Country: Thailand
- City: Pathum Thani
- Study Area: Protein-Ligand Engineering and Molecular Biology laboratory at the National Center for Genetic Engineering and Biotechnology (BIOTEC)
- Parasite’s species: Plasmodium falciparum
Imaging Technique
- Optical Train: Microscope with camera
- Microscope: Olympus BX51 microscope
- Camera: DP71 digital camera
- Magnification: 100×
- Image Resolution: 4080 x 3072
- Number of Images: 23,248 images
Dataset Availability
| Corresponding Author | DOI |
|---|---|
| Kitsuchart Pasupa (kitsuchart@it.kmitl.ac.th) | 10.1109/ACCESS.2020.2990497 |
Cite this Article
❗🛑 If you are using this resource, please cite:
Kudisthalert, Wasu & Pasupa, Kitsuchart & Tongsima, Sissades. (2020). Counting and Classification of Malarial Parasite From Giemsa-Stained Thin Film Images. IEEE Access. PP. 1-1. 10.1109/ACCESS.2020.2990497.