FPGA Implementation of Brain Tumor Detection Using Lifting Based DWT Architectures
Now a days, almost all areas of medical diagnosis are impacted by the digital image processing. When an image is processed for visual interpretation, the human eye is the judge of how well a particular method works. Clinical application demanding Radiotherapy plan, for instance, often benefits from the complementary information in images of different modalities. For medical diagnosis, Computed Tomography (CT) provides the best information on denser tissue with less distortion. Magnetic Resonance Image (MRI) provides better information on soft tissue with more distortion. With more available multimodality medical images in clinical applications,his idea of combining images from different modalities become very important and medical image fusion has emerged as a new promising research. This paper analyzes the characteristics of the Second Generation Wavelet Transform and put forward an image fusion algorithm based on Wavelet Transform. We looked at the selection principles about low and high frequency coefficients according to different frequency domain after wavelet. Then the proposed fused image used to segment the optic disc from the optic region. And then we are implementing the algorithm based on the method of Compensation factor method which is to be usually segmenting the optic discs from the blood vessels. This segmentation process could be effective in the bio medical applications. In this paper, a hardware implementation of a real time fusion system is proposed. The system is based on an Xilinx Spartan 3 EDK FPGA and implements a configurable linear pixel level algorithm which is able to result in color fused images using System C language.