Red Blood Cell Morphology Dataset for Image Classification

The dataset was compiled from multiple sources:

Chula RBC-12-Dataset (Naruenatthanaset et al., 2021):  The dataset includes the following classes: Normal, Macrocyte, Microcyte, Spherocyte, Target cell, Stomatocyte, Ovalocyte, Teardrop, Burr cell, Schistocyte, uncategorized, Hypochromia, and Elliptocyte. 

\url{https://github.com/Chula-PIC-Lab/Chula-RBC-12-Dataset}

ThalassemiaPBS-Dataset (Tyas et al., 2022): This dataset represents nine distinct cell types. 

\url{https://doi.org/10.17632/rfdz6wfzn4.1}

Our samples: This supplementary collection was provided by the Anti-Cancer Centre in El-Oued, Algeria. It contains 13 blood smear images representing five different RBC disorders: Burr cells, Ovalocyte, Teardrop. Schistocyte, and Stomatocyte These samples were provided in May 2024 using an optical microscope at 1000x magnification.

We cropped each blood smear image from the Chula RBC-12 Dataset to cepture single RBCs and relevant ROI. We then categorized them according to their class using the referenced files provided by the authors.

The "Label" folder found in the dataset is structured as follows: x and y coordinates, and the RBC type represented as values from 1 to 11.

We did the same on the samples we got from the ACC. The labelling was done by specialists in the centre.