All-IDB: The acute lymphoblastic leukemia image database for image processing

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. Unfortun...

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Bibliographic Details
Published in2011 18th IEEE International Conference on Image Processing pp. 2045 - 2048
Main Authors Labati, R. D., Piuri, V., Scotti, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2011
Subjects
Acute lymphoblastic leukemia
Blood
Cells (biology)
Classification algorithms
Conferences
image classification
Image segmentation
Microscopy
public image database
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ISBN1457713047
9781457713040
ISSN1522-4880
DOI10.1109/ICIP.2011.6115881

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Summary: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.
ISBN:1457713047
9781457713040
ISSN:1522-4880
DOI:10.1109/ICIP.2011.6115881