Open AccessBrain Tumor Segmentation u sing K Means Clustering and Detection u sing Convolutional Neural Network
Author(s) -
Pandiarajan.K Senthil Nathan.M,
S. B. Pandey,
Khushbu Kumari,
P. Sathishkumar
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.e2855.039520
Subject(s) - convolutional neural network , computer science , artificial intelligence , cluster analysis , segmentation , pattern recognition (psychology) , image segmentation , artificial neural network , brain tumor , computer vision , pathology , medicine
This paper presents brain tumor detection and segmentation using image processing techniques. Convolutional neural networks can be applied for medical research in brain tumor analysis. The tumor in the MRI scans is segmented using the K-means clustering algorithm which is applied of every scan and the feed it to the convolutional neural network for training and testing. In our CNN we propose to use ReLU and Sigmoid activation functions to determine our end result. The training is done only using the CPU power and no GPU is used. The research is done in two phases, image processing and applying neural network.