de Souza Oliveira et al., 2022 Image Dataset

Article Title: A new approach for microscopic diagnosis of malaria parasites in thick blood smears using pre-trained deep learning models

Article Link: ref

Description

It is a thick, Giemsa-stained blood smear image dataset

Demography

• Country: Brazil:earth_americas:
• Study Area: Instituto Nacional de Pesquisa da Amazˆonia (INPA)
• Parasite’s species: Plasmodium vivax

Imaging Technique

• Optical Train: Microscope
• Microscope Type: ZEISS Axio Imager M2 microscope
• Magnification: 100×
• Resolution: 1388 × 1040
• Number of Images: 676

Dataset Availability

Status	Corresponding Author	DOI
Available on Request	C. Ferreira Fernandes Costa Filho (ccosta@ufam.edu.br)	https://doi.org/10.1016/j.bspc.2022.103931

Cite this Article

❗:stop_sign: If you are using this resource, please cite:

Fong Amaris, W.M., Martinez, C., Cortés-Cortés, L.J. et al. Image features for quality analysis of thick blood smears employed in malaria diagnosis. Malar J 21, 74 (2022). https://doi.org/10.1186/s12936-022-04064-2