Loh et al., 2020 Image Dataset
Article Title: A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN
Article Link: ref
Description
It is a Giemsa-stained blood smear image dataset
Demography
- Parasite’s species: Plasmodium falciparum 3D7 strain cultured in a laboratory
Imaging Technique
- Optical Train: Microscope with camera
- Microscope Type: Leica ICC50 W microscope
- Camera Type: Leica digital camera
Dataset Availability
| Corresponding Author | DOI |
|---|---|
| Karupppasamy Subburaj (subburaj@sutd.edu.sg)) | https://doi.org/10.1016/j.compmedimag.2020.101845 |
Cite this Article
❗🛑 If you are using this resource, please cite:
Loh, D. R., Yong, W. X., Yapeter, J., Subburaj, K., & Chandramohanadas, R. (2021). A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN. Computerized Medical Imaging and Graphics, 88, 101845. https://doi.org/10.1016/j.compmedimag.2020.101845