Abstract

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Title:: Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Author(s):: SUN Ying1; ZHANG Yinlong2; WANG Xin3; ZENG Ziming4; MAO Haixia4; 1. Department of Critical Care, the First Hospital of China Medical University, Shenyang 110001, China 2. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3. College of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China 4. School of Automotive and Transportation Engineering, Shenzhen Polytechnic, Shenzhen 518055, China

Keywords:: Keywords: multiple sclerosis lesion segmentation 3D voxel enhancement 3D alpha matting color image segmentation technique

Abstract:: Abstract: Objective To propose a novel method for multiple sclerosis (MS) lesions segmentation in T1-weighted, T2-weighted and fluid-attenuated inversion recovery (Flair) MRI images. Methods MS lesions with high intensity were distinguished from other tissues using 3D image enhancement technology. Then, the false positive volume of interest (VOI) with uneven intensity and density were removed by the false positive reduction method, and the VOI outside the white matter were eliminated by the color image segmentation method. Finally, the color MR technique was used to generate 3 regions to refine MS lesions segmentation. Results The test on CHB dataset showed that the mean true positive rate and mean Dice similarity coefficient reached 0.48 and 0.52. Conclusion The proposed method can not only remove noise and other non-pathological tissues effectively, but also identify and segment MS lesions accurately. Because of its effectiveness and accuracy, the proposed method can provide a basis for the subsequent analysis of MS segmentation technology, and provide on objective and convenient method for the prevention and treatment of MS lesions and disease tracking.