A Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image segmentation

Abstract

This paper describes a new Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image segmentation based on two existing techniques, region-based and level set methods. In our approach, instead of using the typical pipeline methodology to integrate the two techniques, a hybrid set-based methodology will be proposed. To evaluate the effectiveness of HAST, MR images taken from a national hospital that reflects the quality of real world medical images are used. A comparison between the two individual techniques and HAST will also be made to demonstrate the effectiveness of the latter.