Segmentation of Brain Tumor from MRI Using Skull Stripping and Neural Network

  Dimple Kapoor,  R. Kashyap

Brain tumor is an alarming disease if not noticed on time. Several researchers have done their researches in this field to discover some new methods of brain tumor detection. In this paper, we present a method of brain tumor detection from MRI images. Segmentation is done by using Self-Organizing Map (SOM) and Neural network (NN). Stationary Wavelet Transform (SWT) is used to extract the features from an input image before the training process for segmentation. We proposed a new skull stripping algorithm for the purpose of effective skull stripping. We used BRAINIX medical images as a dataset for our method. The proposed method performs better than the methods discussed in the literature. It is easy to implement and robust.

Keywords- Brain Tumor, Neural Network (NN), Segmentation, Self-Organizing Map (SOM), Stationary Wavelet Transform (SWT).

Unique Identification Number - IJEDR1603097
Page Number(s) - 593-598
Pubished in - Volume 4 | Issue 3 | August 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Dimple Kapoor,  R. Kashyap,   "Segmentation of Brain Tumor from MRI Using Skull Stripping and Neural Network", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 3, pp.593-598, August 2016, Available at :http://www.ijedr.org/papers/IJEDR1603097.pdf