BRAIN TUMOUR SEGMENTATION BASED ON LOCAL INDEPENDENT PROJECTION BASED CLASSIFICATION

Priyanka S. Jadhav, Meeta Bakuli

Abstract: Brain tumour detection and segmentation is most important and challenging task in early tumour diagnosis. There are various segmentation methods available but they are still challenging methods because of its complex characteristics such as ambiguous boundaries and high diversity. To overcome this problem we are going to implement automatic brain tumour detection and segmentation method by using local independent projection based classification. In this method we are going to consider tumour segmentation as a classification problem. In this paper locality is important in calculations of projections. Also local anchor embedding is used to solve linear projection weights. The softmax regression model is used to improve classification performance. In this study we used MRI images as training and testing data. Finally the brain tumour is classified into tumour and edema region. The area of tumour region is calculated in pixels.

Keywords: Brain tumour detection & segmentation, local independent projection based classification, local anchor embedding and softmax regression

DOI: https://doi.org/10.15623/ijret.2015.0407002