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Comparison of F-Measure, BER and PSNR of Tumor Detection using Hybridization of Fuzzy and Region Growing
Author(s) -
Simran Arora,
Gurjit Singh,
Vijay Kumar Banga
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015905159
Subject(s) - computer science , measure (data warehouse) , fuzzy logic , artificial intelligence , data mining , pattern recognition (psychology)
This paper has dedicated to brain tumor detection algorithm. The majority of the existing work with tumor detection has neglected the using object-based segmentation. Thus this paper has planned an effective brain tumor detection using the feature detection and roundness metric. To boost the tumor detection rate further we've incorporated the proposed hybridization of fuzzy C-means and region growing segmentation based tumor detection with the use of trilateral filter in its preprocessing stage. The planned method has the capability to generate efficient results even in the event of large occurrence of the noise. The experimental results have obviously shown that the planned method outperforms over the available techniques.

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