Vision-based guidance system for breast awareness application using RGB-D sensor

Breast cancer is one of the most dominant cancers detected among middle-aged women worldwide. In Southeast Asia, Philippines have the highest incidence rate of breast cancer in fact it ranks at number one in incidence and mortality rates among the common cancer in women. Become aware of cancer early...

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Main Authors: Aguilar, Ariane A., Carlos, Kamille Klaire C., Venus, Ma. Joanna C.
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Language:English
Published: Animo Repository 2016
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/6423
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-7067
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-70672022-06-09T06:10:10Z Vision-based guidance system for breast awareness application using RGB-D sensor Aguilar, Ariane A. Carlos, Kamille Klaire C. Venus, Ma. Joanna C. Breast cancer is one of the most dominant cancers detected among middle-aged women worldwide. In Southeast Asia, Philippines have the highest incidence rate of breast cancer in fact it ranks at number one in incidence and mortality rates among the common cancer in women. Become aware of cancer early considerably affects its curability. Breast self-examination (BSE) is an inexpensive, non-invasive and non-hazardous procedure which can be performed by women to observe their own breasts and detect any abnormalities thus can resolve the issue of the presence of the lumps which can be cancerous. Without a medical supervision and guidance from a health professional, BSE is complicated to master. In response to this issue, this research intentions to develop computer vision- based guidance system which can monitor and guide women while they perform BSE. The proposed system requires a Microsoft Kinect and a personal computer. The proposed system is comprised of three categories. The first algorithm is concerned with the identification of breast area using extensive use of object detection using feature cascaded classifier. The second algorithm is concerned on finger presence for every palpated areas, using image annotation and training algorithm and feature classifier. The third algorithm is concerned with depth classification and hand tracking in every palpated areas using the Support Vector Machine and Consensus Matching and Tracking. These algorithms were integrated together to create a complete BSE guidance system with a custom graphical user interface with additional features such as visual and tactile inspection and visual feedback. This research aims to develop the ability of women in performing BSE through the use of the proposed system in order to educate breast awareness among women and eventually reduce the breast cancer mortality rate. 2016-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/6423 Bachelor's Theses English Animo Repository Breast--Cancer Computer vision Breast-- Examination Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Breast--Cancer
Computer vision
Breast-- Examination
Engineering
spellingShingle Breast--Cancer
Computer vision
Breast-- Examination
Engineering
Aguilar, Ariane A.
Carlos, Kamille Klaire C.
Venus, Ma. Joanna C.
Vision-based guidance system for breast awareness application using RGB-D sensor
description Breast cancer is one of the most dominant cancers detected among middle-aged women worldwide. In Southeast Asia, Philippines have the highest incidence rate of breast cancer in fact it ranks at number one in incidence and mortality rates among the common cancer in women. Become aware of cancer early considerably affects its curability. Breast self-examination (BSE) is an inexpensive, non-invasive and non-hazardous procedure which can be performed by women to observe their own breasts and detect any abnormalities thus can resolve the issue of the presence of the lumps which can be cancerous. Without a medical supervision and guidance from a health professional, BSE is complicated to master. In response to this issue, this research intentions to develop computer vision- based guidance system which can monitor and guide women while they perform BSE. The proposed system requires a Microsoft Kinect and a personal computer. The proposed system is comprised of three categories. The first algorithm is concerned with the identification of breast area using extensive use of object detection using feature cascaded classifier. The second algorithm is concerned on finger presence for every palpated areas, using image annotation and training algorithm and feature classifier. The third algorithm is concerned with depth classification and hand tracking in every palpated areas using the Support Vector Machine and Consensus Matching and Tracking. These algorithms were integrated together to create a complete BSE guidance system with a custom graphical user interface with additional features such as visual and tactile inspection and visual feedback. This research aims to develop the ability of women in performing BSE through the use of the proposed system in order to educate breast awareness among women and eventually reduce the breast cancer mortality rate.
format text
author Aguilar, Ariane A.
Carlos, Kamille Klaire C.
Venus, Ma. Joanna C.
author_facet Aguilar, Ariane A.
Carlos, Kamille Klaire C.
Venus, Ma. Joanna C.
author_sort Aguilar, Ariane A.
title Vision-based guidance system for breast awareness application using RGB-D sensor
title_short Vision-based guidance system for breast awareness application using RGB-D sensor
title_full Vision-based guidance system for breast awareness application using RGB-D sensor
title_fullStr Vision-based guidance system for breast awareness application using RGB-D sensor
title_full_unstemmed Vision-based guidance system for breast awareness application using RGB-D sensor
title_sort vision-based guidance system for breast awareness application using rgb-d sensor
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/etd_bachelors/6423
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