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BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE

Mammograms are the best tool to detect an early disease of breast cancer. In mammography, medical experts look for clustered microcalcifications and irregular density masses. As microcalcification is a tiny speck of calcium in breast, it appears as white spot in mammogram. Problem occurred when t...

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Main Author: FADILLULLAH, SITI AISHAH
Format: Final Year Project
Language:English
Published: Universiti Teknologi Petronas 2005
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://utpedia.utp.edu.my/7607/1/2005%20-%20BREAST%20CANCER%20DETECTION%20USING%20COMPUTATIONAL%20INTELLIGENCE.pdf
http://utpedia.utp.edu.my/7607/
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spelling my-utp-utpedia.76072017-01-25T09:46:36Z http://utpedia.utp.edu.my/7607/ BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE FADILLULLAH, SITI AISHAH TK Electrical engineering. Electronics Nuclear engineering Mammograms are the best tool to detect an early disease of breast cancer. In mammography, medical experts look for clustered microcalcifications and irregular density masses. As microcalcification is a tiny speck of calcium in breast, it appears as white spot in mammogram. Problem occurred when the clinician reads the mammograms using a magnifying glass, as it is difficult to detect calcification because there is a wide range of abnormalities and it also due to the small size and their similarity with other tissue structure. One of the problems is to distinguish between malignant and benign tumors. Thus, the objectives of this project are to enhance mammogram image using image processing technique and to provide a pattern recognition system by signifying whether further investigation is needed, therefore it may assist medical expert in detection of breast cancer. Accordingly, the scope of this project is based on the pattern recognition system, which includes preprocessing, feature extraction, and classification. The task for the project is divided into two parts. The first part is the enhancement of the image and the detection of calcification. The second part of the project is to design, develop, and test the network whether it run as expected. As the result, mammogram images have been processed through image processing by using MATLAB, and opening morphological operation has been used for the detection. A pattern recognition system has been developed by the use of neural network. As a conclusion, a successful implementation of pattern recognition system as one way to detect breast cancer could help medical field in diagnosing breast cancer. Universiti Teknologi Petronas 2005-06 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/7607/1/2005%20-%20BREAST%20CANCER%20DETECTION%20USING%20COMPUTATIONAL%20INTELLIGENCE.pdf FADILLULLAH, SITI AISHAH (2005) BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE. Universiti Teknologi Petronas. (Unpublished)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
FADILLULLAH, SITI AISHAH
BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
description Mammograms are the best tool to detect an early disease of breast cancer. In mammography, medical experts look for clustered microcalcifications and irregular density masses. As microcalcification is a tiny speck of calcium in breast, it appears as white spot in mammogram. Problem occurred when the clinician reads the mammograms using a magnifying glass, as it is difficult to detect calcification because there is a wide range of abnormalities and it also due to the small size and their similarity with other tissue structure. One of the problems is to distinguish between malignant and benign tumors. Thus, the objectives of this project are to enhance mammogram image using image processing technique and to provide a pattern recognition system by signifying whether further investigation is needed, therefore it may assist medical expert in detection of breast cancer. Accordingly, the scope of this project is based on the pattern recognition system, which includes preprocessing, feature extraction, and classification. The task for the project is divided into two parts. The first part is the enhancement of the image and the detection of calcification. The second part of the project is to design, develop, and test the network whether it run as expected. As the result, mammogram images have been processed through image processing by using MATLAB, and opening morphological operation has been used for the detection. A pattern recognition system has been developed by the use of neural network. As a conclusion, a successful implementation of pattern recognition system as one way to detect breast cancer could help medical field in diagnosing breast cancer.
format Final Year Project
author FADILLULLAH, SITI AISHAH
author_facet FADILLULLAH, SITI AISHAH
author_sort FADILLULLAH, SITI AISHAH
title BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
title_short BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
title_full BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
title_fullStr BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
title_full_unstemmed BREAST CANCER DETECTION USING COMPUTATIONAL INTELLIGENCE
title_sort breast cancer detection using computational intelligence
publisher Universiti Teknologi Petronas
publishDate 2005
url http://utpedia.utp.edu.my/7607/1/2005%20-%20BREAST%20CANCER%20DETECTION%20USING%20COMPUTATIONAL%20INTELLIGENCE.pdf
http://utpedia.utp.edu.my/7607/
_version_ 1739831485771284480
score 13.211869

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