New decision support tool for acute lymphoblastic leukemia classification

Monica Madhukar; Sos Agaian; Anthony T. Chronopoulos

doi:10.1117/12.905969

2 February 2012 New decision support tool for acute lymphoblastic leukemia classification

Monica Madhukar, Sos Agaian, Anthony T. Chronopoulos

Proceedings Volume 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II; 829518 (2012) https://doi.org/10.1117/12.905969
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

Citation Download Citation

Monica Madhukar, Sos Agaian, and Anthony T. Chronopoulos "New decision support tool for acute lymphoblastic leukemia classification", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 829518 (2 February 2012); https://doi.org/10.1117/12.905969

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