Sampathila et al., 2018 Image Dataset
Article Title: Computational approach for diagnosis of malaria through classification of malaria parasite from microscopic image of blood smear
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Description
It is a thin, Leishman-stained blood smear image dataset.
Demography
- Country: India
- City: Manipal
- Study Area: Haematology Lab, Kasturba Medical College (KMC), Manipal Academy of Higher Education (MAHE), Manipal
- Parasite’s species: Plasmodium vivax
Imaging Technique
- Optical Train: Microscope with camera
- Microscope: Olympus (BX51) Microscope
- Camera: Olympus DP25 digital camera
- Number of Images: 143 images
Dataset Availability
| Corresponding Author | DOI |
|---|---|
| Niranjana Sampathila | 10.4066/biomedicalresearch.29-18-970 |
Cite this article
❗🛑 If you are using this resource, please cite:
Sampathila, Niranjana & Shet, Nagaraja & Basu, Akash. (2018). Computational approach for diagnosis of malaria through classification of malaria parasite from microscopic image of blood smear. Biomedical Research. 29. 10.4066/biomedicalresearch.29-18-970.