Publication Type : Conference Paper
Publisher : 2017 International Conference on Communication and Signal Processing
Source : 2017 International Conference on Communication and Signal Processing (ICCSP), IEEE (2018)
Url : https://ieeexplore.ieee.org/document/8286650
Keywords : Fuzzy C-Means, Kernal Fuzzy C-Means, Level Set method, Spatial Fuzzy C-Means, Spatial Kernel Fuzzy C-Means, Variational Level Set Method
Campus : Mysuru
School : School of Arts and Sciences
Department : Computer Science
Year : 2018
Abstract : Advancements in medical imaging technologies have raised many effective analytical procedures. The promptness in the acquisition and resolution enhancements of the imaging modalities have given a lot more information to the physicians in a less intrusive way about their patients. Active contours are used to the path, segment and make images of an atomic structure matching. To do like that molding functions, that are resulting in the image data and proceeding information about size, shape, and location of this structure are considered. A part of active contour family is invoked from the level set method. The major hindrances of the level setting methods are the loading of controlling constraints and time complexity. The proposed method follows Spatial Kernel Fuzzy C-Means (SKFCM) and Variational Level Set Method (VLSM) to avoid all these imperfections. SKFCM is related to standard Fuzzy C-Means algorithm which makes uses of Gaussian RBF kernel function as a distance metric that incorporates spatial information. The VLSM uses the energy function to govern and scale down the exact processing time that will address the time complexity. The proposed system is a hybrid of both SKFCM and VLSM combined approach. © 2017 IEEE.
Cite this Research Publication : Sudharshan Duth P., Vipuldas C. A., and Saikrishnan V. P., “Integrated spatial fuzzy clustering with variational level set method for MRI brain image segmentation”, in 2017 International Conference on Communication and Signal Processing (ICCSP), 2018.