VISION & LEARNING FOR AUTONOMOUS AI LAB

The LISC database includes the hematological images taken from peripheral blood of healthy subjects. The database has been released to enable comparative evaluation of different techniques on nucleus and cytoplasm segmentation and also recognition of different white blood cells in hematological images.

Samples were taken from peripheral blood of 8 normal subjects and 400 samples were obtained from 100 microscope slides. The microscope slides were smeared and stained by Gismo-Right technique and images were acquired by a light microscope (Microscope-Axioskope 40) from the stained peripheral blood using an achromatic lens with a magnification of 100. Then, these images were recorded by a digital camera (Sony Model No. SSCDC50AP) and were saved in the BMP format. The images contain 720×576 pixels. All of them are color images and were collected from Hematology-Oncology and BMT Research Center of Imam Khomeini hospital in Tehran, Iran. The images were classified by a hematologist into normal leukocytes: basophil, eosinophil, lymphocyte, monocyte, and neutrophil. Also, the areas related to the nucleus and cytoplasm were manually segmented by an expert. P.S: Manual ground truth for only 250 images, has been provided.

The data included in this database can be used, free of charge, for research and educational purposes. Copying, redistribution, and any unauthorized commercial use are prohibited. The use of this database is restricted to those individuals or organizations that obtained the database directly from the first author website. Any researcher reporting results which use this database must acknowledge the LISC database. We request you to do so by citing this publication:
Rezatofighi, S.H., Soltanian-Zadeh, H.: Automatic recognition of five types of white blood cells in peripheral blood. Computerized Medical Imaging and Graphics 35(4) (2011) 333-343.
In addition, we appreciate to hear about any publications that use the LISC database. Feedback on the database is also welcome.

The LISC database can be downloaded from here.