PEMOTONGAN ROI OTOMATIS PADA DIGITAL MAMMOGRAM MENGGUNAKAN OPERASI MORFOLOGI

Authors

  • Januar Adi Putra Institut Teknologi Sepuluh Nopember
  • Nanik Suciati Institut Teknologi Sepuluh Nopember
  • Arya Yudhi Wijaya Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.33197/jitter.vol3.iss1.2016.120

Keywords:

ROI, Digital Mammogram, Morphological Operation

Abstract

[Id]

Salah satu metode yang paling efektif untuk mendeteksi dan mengidentifikasi kanker payudara adalah melalui pemeriksaan mammogram. Keab-normalan kanker payudara dapat dikenali dengan keberadaan massa pada citra mammogram, hal ini dikarenakan massa memiliki tingkat resiko tertinggi dari pada tipe-tipe lainnya. Pada paper ini akan dikemukakan algoritma baru untuk merepresen-tasikan bentuk massa yang tampak pada citra mamogram menggunakan operasi morfologi pada pengolahan citra digital sehingga dapat digunakan untuk analisis kanker payudara. Algoritma disusun tahap demi tahap dengan tujuan memisahkan atau melokalisasi area yang dicurigai terdapat massa kanker payudara untuk mendapatkan Region of Interest (ROI). Telah dilakukan serangkaian ujicoba untuk menguji tingkat kebenaran dari algoritma pemotongan ROI yang diusulkan dimana algoritma usulan terbukti mampu mendeteksi dan mengektraksi ROI pada citra mammogram dengan sangat baik dengan nilai PSNR tertinggi sebesar 0.90 pada kanker payudara ganas dan 0.93 pada kanker payudara jinak.

Kata Kunci: ROI, Digital Mammogram, Operasi Morfologi.

[En]

One of the most effective methods to detect and identify breast cancer is through mammograms. Breast cancer abnormalities can be identified by the presence of a mass on a mammogram image, this is because the masses have the highest risk level of the other types. In this paper we proposed a new algorithm for represent the mass forms that appear on a mammogram image so it can be used for the analysis of breast cancer. Algorithms are prepared step by step with the aim to separate or localize the suspected area there are masses of breast cancer to get a Region of Interest (ROI). Has conducted trials to test the performance of the proposed algorithm to cuts the ROI and the result of proposed algorithm is proven able to detect and extract ROI on a image mammogram with excellent that the high PSNR is 0.90 for malignant cancer and the0.93 for benign cancer.

Keywords : ROI, Digital Mammogram, Morph-ological Operation.

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Published

2016-12-15

How to Cite

[1]
J. A. Putra, N. Suciati, and A. Y. Wijaya, “PEMOTONGAN ROI OTOMATIS PADA DIGITAL MAMMOGRAM MENGGUNAKAN OPERASI MORFOLOGI”, jitter, vol. 3, no. 1, Dec. 2016.

Issue

Vol. 3 No. 1 (2016)

Section

Articles

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