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 |
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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