KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS

Breast cancer was a disease with the condition of the breast tissue became abnormal due to the development of cancer cells in the breast area. One method of breast cancer nondestructive detection was through shooting the indicated breast cancer by using an infrared camera. The emission variations of...

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Main Authors: , Octa Heriana, , Prof. Dr. Ir. Thomas Sri Widodo, DEA
Format: Theses and Dissertations NonPeerReviewed
Published: [Yogyakarta] : Universitas Gadjah Mada 2012
Subjects:
ETD
Online Access:https://repository.ugm.ac.id/100576/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=57122
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spelling id-ugm-repo.1005762016-03-04T08:48:09Z https://repository.ugm.ac.id/100576/ KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS , Octa Heriana , Prof. Dr. Ir. Thomas Sri Widodo, DEA, ETD Breast cancer was a disease with the condition of the breast tissue became abnormal due to the development of cancer cells in the breast area. One method of breast cancer nondestructive detection was through shooting the indicated breast cancer by using an infrared camera. The emission variations of infrared radiation on the image captured showed the level of cancer. The results of infrared camera imaging was called as thermograph image processed in computing for the classification of cancer in breast areas according to the characteristics of each image. The image feature extraction was obtained through the calculation of the fractal dimension of the image by using the box counting algorithm. Image classification process was done by using the Fuzzy C Means algorithm to determine the level of the breast cancer size based on the T component of the TNM system, namely T0, T1, T2 and T3 to the 22 image data to obtain the value of the parameter cluster centers in Fuzzy C Means. The results of test showed that the feature extraction of breast thermography image using box counting fractal method gave the different value between normal breast and inflammatory cancer breast tissues. Normal breast tissue (T0) has fractal dimension mean less than T1, there was about 1.161525 with deviation standar value was about 0.593625. Breast with tumor T1 has fractal dimension mean less than T2, there was about 1.45455 with deviation standar value was about 0.4645. Breast with tumor T2 had fractal dimension mean less than T3, there was about 1.6596 with deviation standar value was about 0.2925,and breast with tumor T3 has fractal dimension mean about 1.81294 with deviation standar value was about 0.20199. The classification using Fuzzy C Means in 32x32 pixel box counting testing showed different result with 64x64 pixel box counting testing, there are 27% differences for cluster = 3, and 45% differences for cluster = 4. [Yogyakarta] : Universitas Gadjah Mada 2012 Thesis NonPeerReviewed , Octa Heriana and , Prof. Dr. Ir. Thomas Sri Widodo, DEA, (2012) KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=57122
institution Universitas Gadjah Mada
building UGM Library
country Indonesia
collection Repository Civitas UGM
topic ETD
spellingShingle ETD
, Octa Heriana
, Prof. Dr. Ir. Thomas Sri Widodo, DEA,
KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
description Breast cancer was a disease with the condition of the breast tissue became abnormal due to the development of cancer cells in the breast area. One method of breast cancer nondestructive detection was through shooting the indicated breast cancer by using an infrared camera. The emission variations of infrared radiation on the image captured showed the level of cancer. The results of infrared camera imaging was called as thermograph image processed in computing for the classification of cancer in breast areas according to the characteristics of each image. The image feature extraction was obtained through the calculation of the fractal dimension of the image by using the box counting algorithm. Image classification process was done by using the Fuzzy C Means algorithm to determine the level of the breast cancer size based on the T component of the TNM system, namely T0, T1, T2 and T3 to the 22 image data to obtain the value of the parameter cluster centers in Fuzzy C Means. The results of test showed that the feature extraction of breast thermography image using box counting fractal method gave the different value between normal breast and inflammatory cancer breast tissues. Normal breast tissue (T0) has fractal dimension mean less than T1, there was about 1.161525 with deviation standar value was about 0.593625. Breast with tumor T1 has fractal dimension mean less than T2, there was about 1.45455 with deviation standar value was about 0.4645. Breast with tumor T2 had fractal dimension mean less than T3, there was about 1.6596 with deviation standar value was about 0.2925,and breast with tumor T3 has fractal dimension mean about 1.81294 with deviation standar value was about 0.20199. The classification using Fuzzy C Means in 32x32 pixel box counting testing showed different result with 64x64 pixel box counting testing, there are 27% differences for cluster = 3, and 45% differences for cluster = 4.
format Theses and Dissertations
NonPeerReviewed
author , Octa Heriana
, Prof. Dr. Ir. Thomas Sri Widodo, DEA,
author_facet , Octa Heriana
, Prof. Dr. Ir. Thomas Sri Widodo, DEA,
author_sort , Octa Heriana
title KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
title_short KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
title_full KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
title_fullStr KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
title_full_unstemmed KLASIFIKASI NONSUPERVISED CITRA THERMAL KANKER PAYUDARA BERBASIS FUZZY C-MEANS
title_sort klasifikasi nonsupervised citra thermal kanker payudara berbasis fuzzy c-means
publisher [Yogyakarta] : Universitas Gadjah Mada
publishDate 2012
url https://repository.ugm.ac.id/100576/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=57122
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