Computer aided diagnosis of breast cancer using image processing techniques and neural networks with logistic regression
Other Title(s)
التشخيص المسند بالحاسوب لسرطان الثدي باستخدام تقنيات معالجة الصور و الشبكات العصبية مع الانحدار اللوجستي
Dissertant
Thesis advisor
Comitee Members
Ababnih, Ismail
al-Hammuz, Sadiq O.
University
Middle East University
Faculty
Faculty of Information Technology
Department
Computer Science Department
University Country
Jordan
Degree
Master
Degree Date
2015
English Abstract
Mammography is the available examination for theearly detectionof signs of breast cancer such as masses, calcifications, bilateral asymmetry and architectural distortion.
Because of the limitation of human observers, computers have a major role in detecting early signs of cancer.
Thewide range of features that defineabnormalities and the fact that they are often indistinguishable from the surrounding tissue make the computer-aided and diagnosis of breast abnormalities a challenge.
This thesis explores ways of using known image processing and machine learning techniques for computer-aided breast cancer detection using mammogram images,with the aim of finding a potentially good method for computer-aided breast cancer detection based on mammogram images, and helps pathologist in decision making.
A concrete application is designed and implemented, including both initial image processing and subsequent cancer detection through the use of machine learning algorithms based on neural networks and logistic regression.
The application isevaluated on a set of mammogram images and the results are presented in detail and discussed.
This thesis is distinguished in using a combination of neural networks and logistic regression in breast cancer detection, as well as the use of real breast cancer images obtained in cooperation with King Hussein Cancer Center.
Main Subjects
Medicine
Information Technology and Computer Science
Topics
No. of Pages
61
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Literature review and previous work.
Chapter Three : Image processing techniques and machine iearning.
Chapter Four : Experimental results and discussion.
Chapter Five : Conclusions and future work.
References.
American Psychological Association (APA)
Sulayman, Raja Faraj Mahmud. (2015). Computer aided diagnosis of breast cancer using image processing techniques and neural networks with logistic regression. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-698682
Modern Language Association (MLA)
Sulayman, Raja Faraj Mahmud. Computer aided diagnosis of breast cancer using image processing techniques and neural networks with logistic regression. (Master's theses Theses and Dissertations Master). Middle East University. (2015).
https://search.emarefa.net/detail/BIM-698682
American Medical Association (AMA)
Sulayman, Raja Faraj Mahmud. (2015). Computer aided diagnosis of breast cancer using image processing techniques and neural networks with logistic regression. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-698682
Language
English
Data Type
Arab Theses
Record ID
BIM-698682
