Automatic Classification and Detection of Brain Tumor with Fuzzy Logic and MFHWT

Authors(1) :-Navjot Jyoti

Brain tumor is connecting abnormal mass of tissue within human brain. The Accurate and early detection of tumor is very necessary for doctors to prevent permanent damage to brain. The main task of the doctors is to detect brain tumor which is time consuming for which they feel burden. So Automatic brain tumor detection is boom to doctors for aiding to diagnose malignant in brain. In the current paper we are going to present the automatic technique by using MFHWT and Fuzzy to detect Tumor. The algorithm present in this paper reduces extraction steps through enhancement the contrast in tumor image by processing the mathematical morphology. The segmentation and the localisation of suspicious regions are performed by applying the region growing marking then feature extraction with MFHWT Finally Fuzzy algorithm is implemented to extract the tumor.

Authors and Affiliations

Navjot Jyoti
Assistant Professor, Department of Computer Science & Engineering, Northwest Group of Institutions, Dhudike, Moga, Punjab, India

Brain Tumor, Detection, Classification, Fuzzy, Harrwave, Segmentation, Mathematical Morphology

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 307-313
Manuscript Number : CSEIT1831296
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Navjot Jyoti, "Automatic Classification and Detection of Brain Tumor with Fuzzy Logic and MFHWT", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.307-313, January-February-2017.
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