Multi-scale zooming of medical image using bicubic filter

Abstract

In this paper, we present an application of the bicubic filter for interpolation of medical images. Our method is based multi-scale medical image interpolation for zooming images. Magnetic resonance "MR" scans diffusion imaging of the brain. Images based on these parameters show potential for use in the differentiation of gray and white matter, edema, and tumor. A bicubic filter was implemented to recognize the tumor in digital images of the brain. This paper describes the basic achievement in the detection of tumors in medical images. The basic concept is that local textures in the images can reveal the typical regularities of the biological structures. The analysis of the level of correction has permitted us to decrease the number of the features to only the significant components. The level of recognition is among three possible types of image area: tumor non-tumor and background. The essential characteristics of the bicubic such as high resolution and accuracy, are exploited to distinguish between the three features. In fact, the concept of distinguishing normal and tumor tissue with MR imaging goes back to the contrast agents, who described substantial differences between normal and cancerous tissue. In gray scale images the determination of the tumor margin based on contrast margin in MRI images makes an unclear view for normal brain tissue and tumor tissue. Multi-scale images are required for obtaining the detection accuracy of the MRI view.