Arshad et al., 2022 Image Dataset
Article Title: A dataset and benchmark for malaria life-cycle classification in thin blood smear images
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Description
It is a thin, Giemsa-stained blood smear image dataset.
Demography
- Country: Pakistan
- City: Lahore
- Parasite’s species: Plasmodium vivax.
Imaging Technique
- Optical Train: Microscope
- Microscope Type: ×SZ-107 series microscope
- Magnification: 100×
- Number of Images: 345 images
Dataset Availability
| Status | Corresponding Author | DOI |
|---|---|---|
| Available on Request | Waqas Sultani (waqas.sultani@itu.edu.pk) | https://doi.org/10.1007/s00521-021-06602-6 |
Cite this Article
❗🛑 If you are using this resource, please cite:
Arshad, Q.A., Ali, M., Hassan, Su. et al. A dataset and benchmark for malaria life-cycle classification in thin blood smear images. Neural Comput & Applic 34, 4473–4485 (2022). https://doi.org/10.1007/s00521-021-06602-6