ABSTRACT
Cervical
cancer is the third major killer disease in developed and developing countries.
Whereas screening and other preventive measures reduce the mortality rate in
developed countries, mortality rates still remain very high in developing
countries. This project focuses on the analysis of a digital image of the
cervix; captured with a low-level camera, under a contrast agent: the visual
inspection with acetic acid (VIA) is known as one of the reference methods to
detect cervical cancer. Gaussian and mean filter techniques were used to remove
the speckles. A segmentation algorithm was used to isolate the region of
interest (ROI) from the image. Additionally a canny edge detection algorithm
was used to find edges. Furthermore, quantification and classification of the
images were done. An Android application was used to integrate all the above.
This allows usage in rural settings. The results obtained were quite
satisfactory (Specificity 79% and Sensitivity of 83%).
CHAPTER ONE
INTRODUCTION
1.0 Background of Study
Cervical
cancer is one of the curable types of cancers in women if detected early. Most
cases
of
cervical cancer are caused as a result of infection with certain types of Human
Papillomavirus (HPV) [4, 6]. Although women who have early exposure to sexual relationships
and those with multiple sexual partners are at high risk of contracting HPV and
eventually, cervical cancer, it is however possible for a woman to be infected
with HPV even if she has had only one sexual partner. In the developed nations,
women above the age of 30, who are at high risk of HPV infection, are given HPV
vaccines, to reduce the chances of having the disease [4]. Traditionally,
optical tests such as VIA, cervicography and colposcopy that employ direct visual
examination of the cervix, are becoming popular as a diagnostic tool.
Healthcare professionals study the cervix at about one minute after applying
the 5% acetic acid to the cervix area. Acetowhite region (AW), which is the
suspected region of cervix, and other vascular abnormalities such as mosaicism,
punctuation and vasculature may appear [4]. Cervical cancer is second only to
breast cancer as the highest cause of cancer-related death of women in the
world [1]. In 2012, it was the fourth leading cause of cancer death in women worldwide
with an estimate of about 65,700 deaths. Unfortunately, up to 90% of these
deaths occurred in the developing nations of the world, especially in
sub-Saharan Africa; 60,100 deaths in Africa, 28,600 in Latin America and the
Caribbean, and 144,400 in Asia. India, the second most populous country in the
world, accounted for 28,600. Latin America and the Caribbean, accounted for 25%
(67,500) of cervical cancer deaths [3]. The main reason for this discrepancy is
the lack of organized, population-wide, screening programmes and medical
personnel to administer and translate various test involved [6]. This thesis
work seeks to address the problem of the lack of medical personnel to
administer and translate various test by coming up with the automation of cervical
cancer detection using digital images of low resolution, deployed on Android
mobile devices.
Department: Computer Science (M.Sc Thesis)
Format: MS Word
Chapters: 1 - 5, Preliminary Pages, Abstract, References, Appendix.
No. of Pages: 84
Price: 20,000 NGN
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