A Medical Image Enhancement Algorithm Based on Topological Derivative and Anisotropic Diusion

I. LARRABIDE; A. A. NOVOTNY; R. A. FEIJÓO; E. TAROCO

Guaraparí

Congreso; XXVI Iberian Latin-American Congress on Computational Methods in Engineering (CILAMCE 2005).; 2005

CILAMCE

Medical imaging techniques like Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound have introduced a formidably powerful tool in medicine. One of the most important stages in medical image computerized analysis is segmentation of objects or definition of their contours. As segmentation results can be heavily affected by image quality and medical images usually present undesired properties like low signal-to-noise (SNR) and contrast-to-noise ratios, as well as multiple and discontinuous edges, image enhancement takes an important roll in the segmentation and analysis process. Although improving imaging techniques (e.g., contrast agents, biological markers) should improve the image quality this is not always enough to give a good result. Much effort has been put into the area of image enhancement. Our aim in this paper is to present a method for medical image enhancement based on the well established concept of topological sensitivity analysis and borrowing image processing techniques like anisotropic diffusion. More specifically, we compute the topological derivative for an appropriate functional associated to the image gradient and a diffusion factor k indicating the cost endowed to a specific image. Further, we propose an image enhancement algorithm based on this approach. Finally, some results are presented in order to show the computational performance of this methodology.