Medical Image Segmentation Based on Wavelet Transformation and Level set method

Segmentation methods have been the subject of much research because they lead to many practical applications. Medical imaging is particularly concerned: it is indeed based on images of the inside of a patient's body (ultrasounds, x-rays, ...) on which it is desired to automatically identify the presence of abnormalities (for example the detection of micro-calcifications in a mammogram may reveal the presence of breast cancer. We can refer to for an overview of the possible applications of wavelets and segmentation problems in medical imaging); but image segmentation is also used in many other areas: shape tracking in video documents, detection of stellar objects in astronomical images, detection of fronts in satellite images for data assimilation in meteorology,....... In this paper, we study a New robust Level Set image segmentation method developed by Wavelet Transformation and Level set model. Proposed algorithm is verified for simulated images and applied for a medical image processing in the MATLAB environment.