Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition
Joint Authors
al-Betar, Mohammed Azmi
Mat Isa, Nor Ashidi
Klaib, Mohammad Fadel
Subhi Al-batah, Mohammad
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract 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.
American Psychological Association (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
Modern Language Association (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
American Medical Association (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
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-452406