Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6181
Title: A Type-2 Fuzzy Image Processing Expert System for Diagnosing Brain Tumors
Authors: Zarinbal, M.
Zarandi, Mohammad Hossein Fazel
Türkşen, İsmail Burhan
İzadi, M.
Keywords: Automated tumor detection system
Medical image processing
Interval type-2 fuzzy set theory
Collaborative fuzzy clustering
Astrocytomas
Issue Date: 2015
Publisher: Springer
Abstract: The focus of this paper is diagnosing and differentiating Astrocytomas in MRI scans by developing an interval Type-2 fuzzy automated tumor detection system. This system consists of three modules: working memory, knowledge base, and inference engine. An image processing method with three steps of preprocessing, segmentation and feature extraction, and approximate reasoning is used in inference engine module to enhance the quality of MRI scans, segment them into desired regions, extract the required features, and finally diagnose and differentiate Astrocytomas. However, brain tumors have different characteristics in different planes, so considering one plane of patient's MRI scan may cause inaccurate results. Therefore, in the developed system, several consecutive planes are processed. The performance of this system is evaluated using 95 MRI scans and the results show good improvement in diagnosing and differentiating Astrocytomas.
URI: https://doi.org/10.1007/s10916-015-0311-6
https://hdl.handle.net/20.500.11851/6181
ISSN: 0148-5598
1573-689X
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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