PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM

Abstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the...

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Main Author: Heru Wahyu Herwanto
Format: Article
Language:Indonesian
Published: Universitas Negeri Malang 2012-09-01
Series:Teknologi dan Kejuruan
Subjects:
Online Access:http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187
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spelling doaj-3b03577e626f4d38831da3fdb2466c322020-11-24T22:51:24ZindUniversitas Negeri MalangTeknologi dan Kejuruan0852-00622477-04422012-09-0131110.17977/tk.v31i1.31872859PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAMHeru Wahyu HerwantoAbstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the edge of suspected mass in mammogram. The method used is an image enhancement and segmentation. The process of image enhancement uses the method of adaptive wavelet enhancement, meanwhile the segmentation uses the calculation of image energy texture with laws filter, smoothing, tressholding, morphology, and boudary extraction. The final result of this method will be compared with those of same method with corrected images abd adaptive histogram equalization. The result of the research shows that there is an improvement of enthropy, deviation standard, and contrast values. The overall execution program takes 1.82869 seconds longer than the adaptive histogram equalization.http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187adaptif wavelet enhancementkanker payudaramassestexture energy
collection DOAJ
language Indonesian
format Article
sources DOAJ
author Heru Wahyu Herwanto
spellingShingle Heru Wahyu Herwanto
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
Teknologi dan Kejuruan
adaptif wavelet enhancement
kanker payudara
masses
texture energy
author_facet Heru Wahyu Herwanto
author_sort Heru Wahyu Herwanto
title PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
title_short PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
title_full PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
title_fullStr PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
title_full_unstemmed PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
title_sort penggunaan wavelet image enhancement dan tekstur energi citra untuk mendeteksi massa mencurigakan pada mamogram
publisher Universitas Negeri Malang
series Teknologi dan Kejuruan
issn 0852-0062
2477-0442
publishDate 2012-09-01
description Abstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the edge of suspected mass in mammogram. The method used is an image enhancement and segmentation. The process of image enhancement uses the method of adaptive wavelet enhancement, meanwhile the segmentation uses the calculation of image energy texture with laws filter, smoothing, tressholding, morphology, and boudary extraction. The final result of this method will be compared with those of same method with corrected images abd adaptive histogram equalization. The result of the research shows that there is an improvement of enthropy, deviation standard, and contrast values. The overall execution program takes 1.82869 seconds longer than the adaptive histogram equalization.
topic adaptif wavelet enhancement
kanker payudara
masses
texture energy
url http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187
work_keys_str_mv AT heruwahyuherwanto penggunaanwaveletimageenhancementdanteksturenergicitrauntukmendeteksimassamencurigakanpadamamogram
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