Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition
المؤلفون المشاركون
al-Betar, Mohammed Azmi
Mat Isa, Nor Ashidi
Klaib, Mohammad Fadel
Subhi Al-batah, Mohammad
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-02-23
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide.
The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective.
Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results.
The developed system consists of two stages.
In the first stage, the automatic features extraction (AFE) algorithm is performed.
In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process.
The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure.
The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL).
The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Subhi Al-batah, Mohammad& Mat Isa, Nor Ashidi& Klaib, Mohammad Fadel& al-Betar, Mohammed Azmi. 2014. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-452406
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Subhi Al-batah, Mohammad…[et al.]. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-452406
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Subhi Al-batah, Mohammad& Mat Isa, Nor Ashidi& Klaib, Mohammad Fadel& al-Betar, Mohammed Azmi. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-452406
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-452406
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر