Hybrid Segmentation Algorithm using M-F based Optimization Model and Modified Fuzzy Clustering
Pavan Kumar Reddy , Dr. K. Fayaz. Srikrishna
Abstract
In this paper, we propose and present an algorithm for medical image segmentation (MIS). By analyzing the current state-of-the-art related algorithms, we introduce the multi-band active contour model based limit function to make the multilayer segmentation available. With the development of image segmentation technology, the development of medical image segmentation technology also got very big, because there is no find common, accepted effect ideal is suitable for medical image segmentation method, almost existing each kind of segmentation method has application in the field of medical image segmentation. Further, with the optimized aims of being robust to the noise and avoiding the bad effluence on the result, we adopt the kernel method and new initialization curve. This model suffers from low noise robustness, and model algorithm is difficult to achieve. Integrated segmentation technology refers to two or more technology is used, combined with their own advantages, so they can on the accuracy or efficiency to as the robustness and effectiveness a concerned, our method is better than the existing medical image segmentation algorithms. Experiment analysis verifies the success of our method.
Medical Image Segmentation (MIS), Kernel Function, Modified Fuzzy Clustering, Multi-band Active Contour Model, Optimization Model.
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[Pavan Kumar Reddy, Dr. K. Fayaz. Srikrishna (2016), Hybrid Segmentation Algorithm using M-F based Optimization Model and Modified Fuzzy Clustering, International Journal of Innovative Research in Computer Science & Technology (IJIRCST), Vol-4, Issue-5, Page No-144-147], (ISSN 2347 - 5552). www.ijircst.org
Pavan Kumar Reddy
Research Scholar, Rayalaseema University, Kurnool, Andhra Pradesh, India
