Eye Melanoma Diagnosis System using Statistical Texture Feature Extraction and Soft Computing Techniques
- سال انتشار: 1402
- محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 13، شماره: 1
- کد COI اختصاصی: JR_JBPE-13-1_009
- زبان مقاله: انگلیسی
- تعداد مشاهده: 51
نویسندگان
Center for Quantum Computational System, Department of Electrical and Electronics Engineering, Adeleke University, Osun State, Nigeria
Department of Medical Imaging, Suzhou Institute of Biomedical and Technology, Chinese Academy of Sciences, Suzhou, ۲۱۵۱۶۳, China
Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Luxembourg
Department of Electrical and Electronics Engineering, Adeleke University, Ede, Nigeria
Department of Biomedical Engineering, Shenzhen University, Shenzhen, China
European Centre for Research and Academic Affairs, Turkey
چکیده
Background: Eye melanoma is deforming in the eye, growing and developing in tissues inside the middle layer of an eyeball, resulting in dark spots in the iris section of the eye, changes in size, the shape of the pupil, and vision. Objective: The current study aims to diagnose eye melanoma using a gray level co-occurrence matrix (GLCM) for texture extraction and soft computing techniques, leading to the disease diagnosis faster, time-saving, and prevention of misdiagnosis resulting from the physician’s manual approach.Material and Methods: In this experimental study, two models are proposed for the diagnosis of eye melanoma, including backpropagation neural networks (BPNN) and radial basis functions network (RBFN). The images used for training and validating were obtained from the eye-cancer database. Results: Based on our experiments, our proposed models achieve ۹۲.۳۱% and ۹۴.۷۰% recognition rates for GLCM+BPNN and GLCM+RBFN, respectively. Conclusion: Based on the comparison of our models with the others, the models used in the current study outperform other proposed models.کلیدواژه ها
Eye Melanoma, Neural Network, Radial Basis Function, Texture Analysis, Diagnostic Errors, Physicians, Models, Eye-Cancer, Neural Network, Computerاطلاعات 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.