| Abstract: | The purpose of this work is to segment the multi region Fluoro Deoxy Glucose radioactivity uptakes from fused Positron Emission Tomography / Computerized Tomography images automatically irrespective of their location in the body. Color image processing is performed to filter and enhance the saturation components of the images. The proposed method of graph cut image partitioning through kernel mapping of the image data is applied for the saturation equalized components of Red, Green, and Blue model images. Energy minimization of the objective function includes the data term minimization within each segmentation region and smoothening the regularization term preserving the boundary regions. Hybrid kernel functions are used for partitioning by graph-cut iterations and computation of region parameters through fixed-point computation. This method combines the performance of global and local kernel functions which makes the segmentation robust and accurate. The performance assessment is carried out for different views of fused Positron Emission Tomography / Computerized Tomography images, and are evaluated qualitatively, quantitatively, and comparatively. This method can be applied for the analysis of certain image features, diagnosis, and display purposes. |
