Automatic brain tissue segmentation using modified K-means algorithm based on image processing techniques

Abstract

Brain tumor, due to uncontrolled development of abnormal cells, is one of the hazardous illnesses that happen in the brain. A fully automatic brain tissue segmentation using improved k means segmentation is discussed in this paper. Generally the brain tumor tissue can appear at any location at different size and shapes. Manual brain tumor detection is not only time-consuming, it is also linked to human errors and depends on the expertise and experience of a medical pathologist. Automatic detection is required in a computer-aided detection system (CAD) for medical images such as MRI. This automatic detection includes pre-processing, segmentation and medical image classification. The preprocessing techniques eliminate noise. Separate the region of interest from the background picture using the segmentation methods. Finally, the classification is conducted to identify brain tumor automatically. The outcomes are also compared between the suggested method and the current methods.