MAFA: Multispectral Adaptive Fuzzy Algorithm for Edge Detection on MRI of Head Scan | Zendy

Humera Tariq | Zendy; Muhammad Shahbaz | Zendy; H Humera | Zendy

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MAFA: Multispectral Adaptive Fuzzy Algorithm for Edge Detection on MRI of Head Scan

Author(s) -

Humera Tariq,

Muhammad Shahbaz,

H Humera

Publication year - 2019

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2019918737

Subject(s) - computer science , multispectral image , head (geology) , artificial intelligence , computer vision , fuzzy logic , enhanced data rates for gsm evolution , edge detection , pattern recognition (psychology) , image processing , image (mathematics) , geology , geomorphology

The purpose of this research is to propose a new Multispectral Adaptive Fuzzy Algorithm (MAFA) for edge detection in Magnetic Resonance Images (MRI). Edge detection is primary pre-segmentation process of MRI. Human structure is envisioned through 3-dimension images provided by MRI. MAFA, 40 Fuzzy Rules based algorithm, is proposed for edge detection because it is efficient in time consumption and processing calculations, effective in results and easier to use than other methods like Canny, Sobel, etcetera. Application of MAFA on 159 images produced sharper and clearer edges than other methods. Average time to process one image is 16 milliseconds which is 61% of time consumed by second best method.

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