Abstract
The proposed work is aimed to develop convolutional neural network (CNN) architecture based computer aided diagnostic system for human brain tumour detection process from magnetic resonance imaging (MRI) volumes. CNN is a class of deep learning networks that are commonly applied to analyse voluminous images. In the proposed method, a CNN model is constructed and trained using MRI volumes of BraTS2013 data. More than 4000 images of normal and tumour slices are used to train the proposed CNN system with 2-layers. The system is tested with about 1000 slices from BraTS and got very accurate results about 90-98% of accuracy. Further, the performance of proposed CNN system is tested by taking a set of clinical MRI volumes of popular hospital. The obtained results are discussed and focused for the future improvement of the proposed system.
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 callMore From: International Journal of Dynamical Systems and Differential Equations
Disclaimer: 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.
