Segmentation of Brain MR Images Using an Improved Charged Fluid Model

• Main Authors: Yu-Sheng Chen, 陳譽升
• Other Authors: Herng-Hua Chang
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/07149608528243610897

碩士 === 國立臺灣大學 === 工程科學及海洋工程學研究所 === 101 === In this thesis, we modify the Charged Fluid Model (CFM) to perform the segmentation of brain magnetic resonance (MR) images. We propose two new stopping forces for the CFM algorithm. Conceptually, the CFM is a simulation of charged fluid, which is like a liquid flowing through and around different obstacles. We divide the process into two steps. First, the CFM flows within the propagating interface until a specified electrostatic equilibrium is achieved. The second step is to evolve the propagating interface based on several image features. Those two procedures are repeated until the propagating front resides on the boundary of objects being segmented. We used this new model for brain MR image segmentation and conducted experiments using a large number of image volumes. The results showed that the new stopping forces can effectively improve the CFM algorithm to segment noisy images as well as real brain MR images.