Region growing and k-means hard clustering technique to extract brain abnormalities in MRI images

Abstract EN

In this work, two adaptive region growing techniques were proposed to isolate and extract any abnormal tissues like tumors, edema and others to aid in detect diseases in MRI images of brain.

Six T1 and T2 weighted images were utilized to test the quality of these proposed techniques.

First adaptive region growing technique involved region growing algorithm followed by contouring process to separate segmented image into two main regions only according to their intensity and then select the abnormality region only.

This technique proved its efficiency to isolate and extract abnormalities correctly without any extra parts of other tissues and for different values of threshold.

The second proposed adaptive technique is implementing region growing algorithm on K-Means clustered image to test its performance and speed.

The results proved the excess in the relative speed of adaptive region growing algorithm besides the high quality performance in extracting tumors.

The programs of this work were achieved utilizing MatLab programming system.-