This repository is an attempt to list all malaria parasite imaging datasets (blood smears).

Current stage: humble beginnings

Contributions welcome! Please report broken links and add new links + citations in the issues or via pull requests!

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  Data: Thin smears; 229 images in total, i.e. 122 Plasmodium falciparum images, 37 P. malariae images, 29 P. ovale and 46 P. vivax images. Image masks designating parasites are given.
  Loddo A., Di Ruberto C., Kocher M., Prod’Hom G. (2019) MP-IDB: The Malaria Parasite Image Database for Image Processing and Analysis In: Lepore N., Brieva J., Romero E., Racoceanu D., Joskowicz L. (eds) Processing and Analysis of Biomedical Information. SaMBa 2018. Lecture Notes in Computer Science, vol 11379. Springer, Cham

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  Data: 1182 images of thick smears, parasite bounding boxes given in xml format
  J.A. Quinn, R. Nakasi, P.K. Mugagga, P. Byanyima, W. Lubega, A. Andama. Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics. Proceedings of the International Conference on Machine Learning for Health Care, Journal of Machine Learning Research W&C track, Volume 56, 2016.

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  Data: 27,558 images of individual cells (infected/ uninfected RBCs) segmented from thin blood smears
  Sivaramakrishnan Rajaraman, Sameer K. Antani, Mahdieh Poostchi, Kamolrat Silamut, Md. A. Hossain, Richard J. Maude, Stefan Jaeger, and George R. Thoma. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images., PeerJ., 2018.

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  655 images of thin smears with bounding boxes around parasites
  Tek FB, Dempster AG, Kale I, Parasite detection and identification for automated thin blood film malaria diagnosis. Computer Vision and Image Understanding 2010, 114:21-32.

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  Data: 1364 images (~80,000 cells)
  Hung J, Goodman A, Lopes S, Rangel G, Ravel D, Costa F, Duraisingh M, Marti M, Carpenter A. Applying Faster R-CNN for Object Detection on Malaria Images., arxiv, 2018.
  The authors want you to cite this other paper