Deteksi Granuloma Melalui Citra Radiograf Periapikal Dengan Metode GLCM Dan Klasifikasi Learning Vector Quantization

Authors

  • Anin Maghfiroh Prodi S1 Teknik Telekomunikasi, Fakultas Teknik Elektro, Universitas Telkom Bandung
  • Bambang Hidayat Prodi S1 Teknik Telekomunikasi, Fakultas Teknik Elektro, Universitas Telkom Bandung
  • Suhardjo Sitam Prodi S1 Kedokteran Gigi, Fakultas Kedokteran Gigi, Universitas Padjajaran Bandung

Keywords:

radiograph periapical, granuloma, GLCM, LVQ

Abstract

Teeth are the hardest parts in the mouth. .One of dental abnormalities that are often found is granuloma. A doctor can detect disease in human’s teeth through the results of x-rays but in its development x-ray are still not able to generate proper diagnosis. On this research will develop an application that can detect granuloma deases with an output on spatial domain with an extraction feature using GLCM which is tabulated by how often different combination of pixel brightness values occur in the image as the method. The classification processed by using LVQ. The classification purpose to classify the image into two conditions, namely: normal and granuloma. The purpose of this research is to facilitate dentist all around Indonesia’s region to detect dental granuloma by radiology tool with affordable price. . The obtained result is a program with a matlab software with Graphical User Interface designed to simplify user application.

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References

Buana, Q. N. (2016). Pengolahan Citra Deteksi Granuloma Melalui Periapical Radiograf Dengan Metode Transformasi DCT dan Linear Discriminant Analysis Berbasis Android. Telkom University.

Damanik, V. O. (2016). Pengolahan Citra Radiograf Periapikal Pada Deteksi Penyakt Granuloma Dengan Metode Multiwavelet Berbasis Android. Telkom University.

Elsevier. (2014). Kamus Kedokteran Dorland. Singapore: Elsevier.

Firdausy, Y. (2012). Deteksi Kista Periapical Pada Gigi Manusia Melalui Citra Dental Periapical Radiograph Dengan Metode Contourlet dan LVQ (Learning Vector Quantization). Telkom University .

Nwamadi, O., Zhu, X., & Nandi, A. K. (2011). Dynamic Physical Resource Block Allocation Algorithms for Uplink Long Term Evolution. IET Communications, 5(7), 1020-1027.

Parker, J. (2011). Algorithms For Image Processing And Computer Vision. Indianapolis: Wiley Publishing.

R.H. Sianipar, H. S. (2013). MATLAB Untuk Pemrosesan Citra Digital . Bandung: Informatika.

Wibowo, S. A. (2016). Simulasi Dan Analisis Pengenalan Citra Daging Sapi Dan Daging Babi Dengan Metode GLCM .Telkom University.

Published

2018-01-18

How to Cite

[1]
A. Maghfiroh, B. Hidayat, and S. Sitam, “Deteksi Granuloma Melalui Citra Radiograf Periapikal Dengan Metode GLCM Dan Klasifikasi Learning Vector Quantization”, SENTER, pp. 298-307, Jan. 2018.