Diagnosing the Leukemia using Faster Region based Convolutional Neural Network
It is difficult to building deep learning algorithms for identifying chronic diseases. One of the must difficulties facing the system of diagnosing leukemia is the irregular shape and twisted nucleus in white blood cells (WBCs) without cleaning and segmentation of cells by Appling filters. Moreover, it is challenge to identify and classify the WBC at once time which is considered the essential step of leukemia diagnosing. This paper proposed system only based on deep learning algorithms. The modified Faster R-CNN (Faster Region based-Convolutional Neural Networks) algorithm is used to detect and classify WBCs. The system is achieved a high accuracy training on the database tacked directly from microscope which used in .
Faster Region CNN, White Blood Cells, Deep Learning, Classification, Detection
SHAKIR M. ABAS
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