title: An improved FCM medical image segmentation algorithm based on MMTD.
abstract: Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM) is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD) and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.
authors.affiliation: Computer School, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
authors.forename: Ningning
authors.initials: N
authors.lastname: Zhou
authors.affiliation: NARI Technology Development Co., Ltd., Nanjing 210061, China.
authors.forename: Tingting
authors.initials: T
authors.lastname: Yang
authors.affiliation: Computer School, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
authors.forename: Shaobai
authors.initials: S
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D059629:Signal-To-Noise Ratio; D012984:Software