Image filtering using Anisotropic Diffusion for Brain tumor detection

Abstract

Abstract A crucial component of medical application is brain tumor analysis. It provides a significant quantity of structural and practical information, which simplifies disease diagnosis and treatment planning. Early tumor diagnosis improves treatment outcomes and ensures the patient's survival. The difficulty of manually segmenting many magnetic resonance pictures increases the likelihood of human error. Therefore, higher accuracy computer-aided detection is required for rapid tumor identification. Using anisotropic diffusion filtering, Otsu threshold segmentation, and morphological procedures, respectively, this work offers computer-aided (CAD) techniques for noise reduction, segmentation, and detection of tumor area in MR images. Additionally, the simulation outcomes demonstrate that anisotropic diffusion and otsu thresholding excels above all other filtering and segmentation combination.