Krappe et al., 2017 Image Dataset
Article Title: Automated plasmodia recognition in microscopic images for diagnosis of malaria using convolutional neural networks
Article Link: ref
Description
It is a thick, blood smear image dataset
Demography
- Country: Germany
- Study Area: Bernhard Nocht Institute for Tropical Medicine (BNITM)
- Parasite’s species: Plasmodium malariae, Plasmodium falciparum, Plasmodium vivax
- Number of parasites: 44
Imaging Technique
- Optical Train: Microscope
Dataset Availability
| DOI |
|---|
| https://doi.org/10.1117/12.2249845 |
Cite this article
❗🛑 If you are using this resource, please cite:
Sebastian Krappe, Michaela Benz, Alexander Gryanik, Egbert Tannich, Christine Wegner, Marc Stamminger, Thomas Wittenberg, Chrisitan Münzenmayer, "Automated plasmodia recognition in microscopic images for diagnosis of malaria using convolutional neural networks," Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 101400B (1 March 2017); https://doi.org/10.1117/12.2249845