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Variational level set and level set method for mri brain image segmentation: A review

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/8286649

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 : Analytical techniques have been effectively risen due to the advancement in medical imaging technologies. Physicians tactlessly get more information about their patients due to the improvements in technology on medical field. In order to segment, identifying similarities and tracking image of a minute structure which modifies restraints which is derived from an image data composed, which have preceding knowledge about its position, mass and outline, we make use of Active Contours. The Level Set method used here is a fragment of active contours. Initializing the regulatory constraints and time complexity are the leading hindrances of level set method. In order to overcome these drawbacks, Variational Level Set Method (VLSM) and Spatial Kernel Fuzzy C-Means (SKFCM) have been included in the proposed model. RBF kernel function is used as a distance metric by Fuzzy C-Means (FCM) algorithm which acts as a standard for SKFCM. Time complexity which is addressed by the actual processing time is reduced and governed by VLSM energy function. SKFCM and VLSM is combined in the proposed system in order to form a cross breed approach.

Cite this Research Publication : Sudharshan Duth, P., Saikrishnan, V.P., Vipuldas, V.P., "Variational level set and level set method for mri brain image segmentation: A review," Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, 2018-January, pp. 1555-1558.

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