Computer Based Acute Leukemia Classification
A. Farag · 2006
In this paper, a set of spatial domain features are extracted from the blood cells image to determine whether a tumor is acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML). This problem is interesting because ALL and AML require different chemotherapy regimens. Proper classification greatly increases the likelihood of remission. The extracted features by the proposed methods are exploited to classify regions of interest (ROI's) into AML or ALL. A three-layer back-propagation neural network is used as a classifier. The results of the neural network for the extracted features are evaluated by calculating the classification rate compared to other techniques. The proposed technique is shown to be superior to the conventional methods with respect to classification accuracy and computational complexity