Implementation of Brain Tumor Segmentation System for Area Calculation of Tumor in Brain MR Images by use of K-Mean Clustering and Fuzzy C-Mean Algorithm

Prof. Dilip Kumar Gandhi; Sunil Tukaram Bhoi; Prof. Sandip Nemade

Medical image analysis is an important biomedical application, which is highly computational in nature and requires the aid of the automated systems.In this paper, a simple algorithm for detecting the shape of tumor in brain MR Images is described. Brain tumor, is an intracranial solid neoplasm. They are created by an abnormal and uncontrolled cell division. Magnetic resonance imaging (MRI) is another modern diagnostic imaging technique that produces cross-sectional images of brain. Unlike CT scans, MRI works without radiation. The MRI tool uses magnetic fields and a sophisticated computer to take high-resolution pictures of brain soft tissues. These images are visually examined by the physician for detection {&} diagnosis of brain tumor. So as assist to physician for calculate correct shape of tumor, this project uses computer aided method for detection of brain tumor.This method allows the segmentation of tumor tissue with accuracy using two algorithms. In addition, it also reduces the time for analysis. At the end gives result as tumor is extracted from the MR image and the shape also determined. The stage of the tumor is examined based on the amountof area calculated from the cluster.

Select Volume / Issues:

• Volume 4 Issue 5, Sept. 2013

Year:

2013

Type of Publication:

Article

Keywords:

Magnetic Resonance Imaging MRI; Brain Tumor; K Means; Fuzzy C Means

Journal:

IJECCE

Volume:

4

Number:

5

Pages:

1421-1424

Month:

September