Abstract
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 [4].
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
