A Level Set Method for Cardiac Magnetic Resonance Image Segmentation: An Adaptive Approach

Abstract

Heart failures are of increasing importance due to increasing life expectation. For clinical diagnosis parameters for the condition of hearts are needed and can be derived automatically by image processing. Accurate and fast image segmentation algorithms are of paramount importance for a wide range of medical imaging applications. Level set algorithms based on narrow band implementation have been among the most widely used segmentation algorithms. The narrow band level set method is a kind of technique that tracks the evolving interface. Its computation domain is set near the zero level set. In this work, we present an adaptive method to extract the left ventricle (LV) irrespective of the intensity variation in heart MR data using a narrow-band level set method. Instead of using the image directly, its scaled down versions are used removing the unnecessary redundancies and extra computations. Also, we suggest an automatic approach for gaussian parameter selection.