Intuitionistic Fuzzy Segmentation of Brain MRI

Suzelawati Zenian and Norhafiza Hamzah and Nur Batrisyia Ahmad Azmi (2021) Intuitionistic Fuzzy Segmentation of Brain MRI. Transactions on Science and Technology, 8 (3-3). pp. 527-532. ISSN 2289-8786

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Abstract

Intuitionistic fuzzy set (IFS) involves the concept of non-membership degree and hesitation degree. The application of IFS is crucial in medical imaging as the images are poor in illumination as well as the structure is hard to detect. This work is focusing on segmenting brain MRI images by using advanced fuzzy and ordinary fuzzy theory. One of the intentions in image segmentation is to divide the regions in an image so that it is easier to be analyzed as it extracts meaningful information. In addition, the main highlight in this work is to apply IFS concept in focal brain parenchymal lesions image segmentation. The method is known as intuitionistic fuzzy c-mean (IFCM). Furthermore, the output images by using IFCM and fuzzy c-mean (FCM) are compared. Based on the results, IFCM has better outcomes in term of accuracy and performance test compared to FCM. Hence, the IFCM has better results in segmenting the focal brain parenchymal lesions images compared to FCM since it is able to preserve the surrounding structure of the brain.

Item Type: Article
Uncontrolled Keywords: Intuitionistic fuzzy set , Ordinary fuzzy set , Segmentation , C-mean , Medical imaging
Subjects: R Medicine > RC Internal medicine > RC31-1245 Internal medicine > RC71-78.7 Examination. Diagnosis Including radiography
T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: FACULTY > Faculty of Science and Natural Resources
Depositing User: SITI AZIZAH BINTI IDRIS -
Date Deposited: 26 Feb 2022 06:25
Last Modified: 26 Feb 2022 06:25
URI: http://eprints.ums.edu.my/id/eprint/31739

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