Brain Tumor Segmentation using Hierarchical Combination of Fuzzy Logic and Cellular Automata
- سال انتشار: 1401
- محل انتشار: مجله سیگنالها و سنسورهای پزشکی، دوره: 12، شماره: 3
- کد COI اختصاصی: JR_JMSI-12-3_008
- زبان مقاله: انگلیسی
- تعداد مشاهده: 143
نویسندگان
Finetech in Medicine Research Center, School of Medicine, Iran University of Medical Sciences (IUMS), Tehran, Iran- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences (IUMS), Tehran, Iran
Neuroimaging and Analysis group, Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute, Tehran University of Medical Sciences, Tehran, Iran- Department of Medical Physics & Biomedical Engineering, School
Department of Bioengineering, Northeastern University, Boston, Massachusetts, USA
Department of Radiology, Sari School of Allied Medical Sciences, Mazandaran University of Medical Sciences, Sari, Iran
چکیده
Background: Magnetic resonance (MR) image is one of the most important diagnostic tools for brain tumor detection. Segmentation of glioma tumor region in brain MR images is challenging in medical image processing problems. Precise and reliable segmentation algorithms can be significantly helpful in the diagnosis and treatment planning. Methods: In this article, a novel brain tumor segmentation method is introduced as a postsegmentation module, which uses the primary segmentation method’s output as input and makes the segmentation performance values better. This approach is a combination of fuzzy logic and cellular automata (CA). Results: The BraTS online dataset has been used for implementing the proposed method. In the first step, the intensity of each pixel is fed to a fuzzy system to label each pixel, and at the second step, the label of each pixel is fed to a fuzzy CA to make the performance of segmentation better. This step repeated while the performance saturated. The accuracy of the first step was ۸۵.۸%, but the accuracy of segmentation after using fuzzy CA was obtained to ۹۹.۸%. Conclusion: The practical results have shown that our proposed method could improve the brain tumor segmentation in MR images significantly in comparison with other approaches.کلیدواژه ها
Cellular automata, fuzzy, glioma, segmentationاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.