MOBILE BASED IMAGE ANALYSIS SYSTEM FOR CERVICAL CANCER DETECTION
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MOBILE BASED IMAGE ANALYSIS SYSTEM FOR CERVICAL CANCER DETECTION
Chapter One:
Introduction
1.0 Background of the Study
Cervical cancer is one of the most treatable tumours in women if diagnosed early. Cervical cancer is mostly caused by HPV infections [4, 6]. Women with early sexual exposure and several partners are more likely to get HPV and develop cervical cancer.
However, even with only one sexual partner, a woman can become infected with HPV. In affluent countries, women over 30 with a high risk of HPV infection are given vaccines to minimise the disease [4].
Optical tests like VIA, cervicography, and colposcopy, which examine the cervix directly, are increasingly used as diagnostic tools. Healthcare experts examine the cervix after applying 5% acetic acid for approximately one minute.
Cervical anomalies, including acetowhite region (AW), mosaicism, punctuation, and vasculature, may be observed [4].
Cervical cancer is the second leading cause of cancer-related death among women worldwide, after breast cancer [1]. In 2012, it was the fourth largest cause of cancer death in women globally, with an estimated 65,700 fatalities.
Up to 90% of deaths occurred in underdeveloped countries, particularly in Sub-Saharan Africa (60,100), followed by Latin America and the Caribbean (28,600), and Asia (144,400). India, the world’s second most populated country, accounting for 28,600. Latin America and the Caribbean were responsible for 25% of cervical cancer mortality (67,500) [3].
The main explanation for the disparity is a paucity of population-wide screening programmes and medical personnel to perform and translate numerous tests [6].
This thesis aims to reduce the need for medical workers to administer and translate tests by automating cervical cancer screening utilising low-resolution digital photos on Android mobile devices.
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1.1 Statement of the Problem
Sub-Saharan Africa accounts for about 80% of cervical cancer-related fatalities among women. The lack of resources for early detection and medical experts to analyse results is a major contributing factor.
We need to create an Android app that analyses and classifies digital cervix images. This will be especially valuable in locations with limited or no medical specialists.
1.2 Motivation and Purpose.
Mobile computing has recently become a valuable tool in healthcare [5]. These devices are becoming increasingly popular due to their portability and low pricing. We are unaware of any existing work on deploying an automated cervical cancer detection technology on mobile platforms.
1.3 Research contribution
A lot of study has been conducted on digital imaging for cervical cancer screening.
This thesis uses digitised photos from a low-resolution mobile device’s camera and an Android app to automate cervical cancer detection.
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