Paper Info
Title
New Decision Support Tool For Acute Lymphoblastic Leukemia Classification
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.
Year
DOI
Venue
2012
10.1117/12.905969
IMAGE PROCESSING: ALGORITHMS AND SYSTEMS X AND PARALLEL PROCESSING FOR IMAGING APPLICATIONS II
Keywords
Field
DocType
Classification, Acute Lymphoblastic Leukemia, Segmentation, Feature Extraction
Leukemia,Computer vision,Lymphoblastic Leukemia,Segmentation,Decision support system,Feature extraction,Treatment intensity,Correlation,Artificial intelligence,Cluster analysis,Physics
Conference
Volume
ISSN
Citations 
8295
0277-786X
4
PageRank 
References 
Authors
0.58
11
3
Name
Order
Citations
PageRank
Monica Madhukar1161.80
Sos Agaian26716.48
Anthony T. Chronopoulos352350.61