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This study proposes and evaluates the application of two classifiers: decision tree (DT) and neural network (NN) to discriminate three region types: cancer (CC), lymphocyte (LC), and stromal (SC) in the breast cancer cell images. The feature extraction from area based texture information of BCCI is studied to compare results from the segmented cells. A combination between texture features based on...
To explore application of fractal analysis to study texture features of microscopic images, a critical exponent analysis (CEA) method is proposed to improve classification ability of histological structures in microscopic breast cancer images based on one-dimensional (1D) sequences. Fractal analysis is commonly a mathematical tool for handling with a complex system. A method of estimating fractal...
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