Maity et. al., 2020 Image Dataset

Article Title: Quantification of malaria parasitaemia using trainable semantic segmentation and capsnet.

Article Link: ref

Description

It is a thin blood smear image dataset.

Demography

• Country: India
• City: West Bengal
• Study Area: Midnapore Medical College and Hospital (MMCH), West Bengal
• Gender: Females and Males
• Age: 10 - 60 years old
• Parasite’s species: Plasmodium vivax and Plasmodium falciparum

Imaging Technique

• Optical Train: Microscope
• Magnification: 100×
• Image Resolution: 0.054 μm pixel
• Number of Images: 210 images
  • P. falciparum: 90
  • P. vivax: 120

Dataset Availability

Corresponding Author	DOI
Maitreya Maity (maitreya@iitkgp.ac.in)	https://doi.org/10.1016/j.patrec.2020.07.002

Cite this Article

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

Maity, Maitreya & Jaiswal, Ayush & Gantait, Kripasindhu & Chatterjee, Jyotirmoy & Mukherjee, Anirban. (2020). Quantification of malaria parasitaemia using trainable semantic segmentation and capsnet. Pattern Recognition Letters. 138. 10.1016/j.patrec.2020.07.002.