IDENTIFIKASI KEBERADAAN KANKER PADA CITRA MAMMOGRAFI MENGGUNAKAN METODE WAVELET HAAR

Putra, Dane Kurnia and Santoso, Imam and Zahra , Ajub Ajulian (2011) IDENTIFIKASI KEBERADAAN KANKER PADA CITRA MAMMOGRAFI MENGGUNAKAN METODE WAVELET HAAR. Undergraduate thesis, Jurusan Teknik Elektro Fakultas Teknik.

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Abstract

Breast cancer is the most common kind of cancer suffered by women. Mammography has been a common method for early detection of breast cancer. Recently mammograms are examined manually, so it demands good knowledge, intuition, and experience in this particular field. In many cases the breast normal tissue can hide malignant so that it can’t b seen on the mammogram. With image processing tissue into mammogram image can be effored to know location. Much methode are used in digital image processing. Methode is used in this final task is texture analysis. Based on that methode, this simulation program is made for identification tissue into mammogram image using wavelet Haar methode. Data about mammogram image any 42 image are get from Telogorejo Hospital Semarang. This program simulation is started with reading image processing and then continued to ROI process, in image from ROI used image enhancement quality with median filter to strech the contrast, after that texture analysis is used to get coefficient from that image. The classification is started with the decomposition process to obtain the wavelet coefficients which then counted the energy and entropy values of each images and then incorporated to database. The next process is comparing the energy and entropy between images which will be classified with the images on the database. The final step is to find Euclidean distance to show that the tested images is one of the class on the database. From the 42 sample observed, the testing result image after ROI and enhancement show that it has recognition rate 86% and testing result without image enhancement show recognition rate at 50%. The observed with using image enhancement ang wavelet Haar from 14 normally image, 13 image can identified, from 20 masses image, 15 can identified, from 8 microclasification image, 7 can identified. The observed without image enhancement and wavelet Haar is using 10 image analyzed by doctor. from 2 normally image, 1 image can identified, from 6 masses image, 2 can identified, from 2 microclasification image, 2 can be identified as microclassification. Keywords: breast cancer, wavelet Haar, decomposition, energy, Euclidean.

Item Type:Thesis (Undergraduate)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Faculty of Engineering > Department of Electrical Engineering
Faculty of Engineering > Department of Electrical Engineering
ID Code:25529
Deposited By:Mr. Sudjadi Pranoto
Deposited On:13 Jan 2011 15:29
Last Modified:13 Jan 2011 15:29

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