Segmentation of Cerebral Tumors Using Coactive Transform Approach
K. SelvaBhuvaneswari, Pamidimukkala Sai Geetha · 2012
The main topic of this work is to segment brain tumors based on a hybrid approach. For tumor segmentation a coactive approach of wavelet and watershed transform is proposed. If only watershed algorithm be used for segmentation of image, then over clusters in segmentation is obtained. To solve this, an approach of using wavelet transformer is proposed to produce initial images, then watershed algorithm is applied for the segmentation of the initial image, then by using the inverse wavelet transform, the segmented image is projected up to a higher resolution.Even MR images are noise free, usage of wavelet decomposition involving a low-pass filter decreases the amount of the minute noise if any in the image and in turn leads to a robust segmentation. The results demonstrate that combining wavelet and watershed transform can help us to get the high accuracy segmentation for tumor detection.