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ALL-IDB : the acute lymphoblastic leukemia image database for image processing

By R. Donida Labati, V. Piuri and F. Scotti


The visual analysis of peripheral blood samples is an important test in the procedures for the diagnosis of leukemia. Automated systems based on artificial vision methods can speed up this operation and increase the accuracy and homogeneity of the response also in telemedicine applications. Unfortunately, there are not available public image datasets to test and compare such algorithms. In this paper, we propose a new public dataset of blood samples, specifically designed for the evaluation and the comparison of algorithms for segmentation and classification. For each image in the dataset, the classification of the cells is given, as well as a specific set of figures of merits to fairly compare the performances of different algorithms. This initiative aims to offer a new test tool to the image processing and pattern matching communities, direct to stimulating new studies in this important field of research

Topics: Acute lymphoblastic leukemia, public image database, image segmentation, image classification, Settore INF/01 - Informatica
Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
Year: 2011
DOI identifier: 10.1109/ICIP.2011.6115881
OAI identifier:

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