Muhammad et al., 2025 Image Dataset
Article Title: Morphology classification of malaria infected red blood cells using deep learning techniques
Article Link: ref
Description
It is a thin, Giemsa-stained blood smear image dataset.
Demography
- Country: Nigeria
- City: Kano
- Study Area: Asiya Bayero pediatric hospital, kano state, Nigeria & Murtala Muhammad specialist hospital
- Number of patients: 100 patients
Imaging Technique
- Optical Train: Smartphone appended to a microscope eyepiece
- Image Resolution: 750 x 750
- Smartphone: 12MP iPhone 10 camera
- Number of Images: 24712 images
Dataset Availability
| Status | Dataset Link | DOI |
|---|---|---|
| Publicly available | Dataset | 10.1016/j.bspc.2024.106869 |
Cite this article
❗🛑 If you are using this resource, please cite:
Fatima Abdullahi Muhammad, Rubita Sudirman, Nor Aini Zakaria, Syarifah Noor Syakiylla Sayed Daud, Morphology classification of malaria infected red blood cells using deep learning techniques, Biomedical Signal Processing and Control, Volume 99, 2025, 106869, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2024.106869.