Image processing of periapical radiograph on granuloma detection by analysis method based on Android
Abstract
Objectives: The study assesses periapical radiograph image with various android based analysis method to detect granuloma.Materials and Methods: The study uses survey descriptive cross sectional by using questionnaire. The questionnaire is distributed to 70 random respondents. The methods of the android application used are BLOB (Binary Large Object), DCT and LDA (Discrete Cosine Transform and Linier Discriminant Analysis), DWT and PCA (Discrete Wavelet Transform & Principal Component Analysis), and multiwavelet transformation. The questionnaire assessment included accuracy, effectiveness, attractiveness, innovativeness of the android application.
Results: Android application with BLOB has effectivity and accuracy of 62,5%, attractiveness and innovativeness of 75%. Android application with DCT and LDA has effectivity and accuracy of 50 %, attractiveness of 70% and innovativeness of 80%. Android application with DWT and PCA has effectivity of 50%, accuracy of 60%, attractiveness of 66,66% and innovativeness of 80%. Android application with multiwavelet transformation has effectivity and accuracy of 50%, attractiveness of 55% and innovativeness of 73%.
Conclusion: Based on assessment, the four methods used to detect granuloma are effective and applicative with android-based application. Android-based Application can detect granuloma with approximately more than 70% successful rate. These methods ease the practitioner to interpret the granuloma image.
References
White SC, Pharoah MJ. Oral Radiology: Principles and Interpretation. 6th ed. St.Louis: Mosby; 2009.
Thomas A, Firman RN, Azhari A. Analisis radiograf periapikal menggunakan software ImageJ pada granuloma periapikal pada perawatan endodontik. Maj Kedokt Gigi Indones. 2017;3(2):105-10.
Margono G. Radiografi Periapikal Untuk Mendukung Perawatan Dalam Kedokteran Gigi. Jurnal PDGI Edisi Khusus Tahun ke-52. Jakarta: Fakultas Kedokteran Gigi Usakti; 2002.
Grossman LI, Oliet S, Del Rio CE. Ilmu Endodontik dalam Praktek, 11th ed., Prof. drg Sutatmi Suryo, Ed. Jakarta: Perpustakaan Nasional; 1995.
Garg N, Garg A. Textbook of Endodontics. New Delhi: Ajanta Offset & Packagings Ltd.; 2007. p.41.
Sitam S. Radiografi Periapikal. EGC; 2013.
Shridar B, Prasad DV. Finding 3D Teeth Positions by Using 2D Uncalibrated Dental X-Ray Images. Blenkinge Institute of Technology; 2010.
Kadir A, Susanto A. Teori dan Aplikasi Pengolahan Citra. Yogyakarta: ANDI, 2013.
Amalina N. Simulasi Matlab pada Deteksi Penyakit Gigi Granuloma Menggunakan Principal Component Analysis dan S-Transform Melalui Radiograf Periapikal dengan Metoda Radial Basis Function. Bandung: Universitas Telkom; 2014.
Utami NP. Deteksi Granuloma melalui Citra Periapikal Radiograf dengan Menggunakan Metode K-NN (K-Nearest Neighbour) pada Aplikasi Android (Skripsi). Bandung: Universitas Telkom; 2014.
Annisa A. Simulasi dan Analisis Deteksi Abses Periapikal Menggunakan Transformasi DWT (Discrete Wavelet Transform) dan metode PCA (Principal Component Analysis). Bandung: Universitas Telkom; 2014.
Gemintang RS, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal pada Deteksi Penyakit Granuloma dengan Metode Binary Large Object Berbasis Android. e-Proceeding of Engineering 2017;4(1):106-14.
Wijayanti LA, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal Pada Deteksi Penyakit Granuloma Menggunakan Metode Discrete Wavelet Transform & Principal Component Analysis Berbasis Android. e-Proceeding of Engineering 2017;4(1):333-9.
Damanik VO, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal Pada Deteksi Penyakit Granuloma Dengan Metode Multiwavelet Berbasis Android. e-Proceeding of Engineering 2017;4(1):547-54.
Buana QN, Hidayat B, Sitam S. Pengolahan Citra Deteksi Granuloma Melalui Periapical Radiograf Dengan Metode Transformasi Dct Dan Linier Discriminant Analysis Berbasis Android. e-Proceeding of Engineering 2017;4(1):367-71.
MATLAB Image Processing Toolbox User Guide. The Math Works Inc. 2002.
Zardi A. Klasifikasi Kanker Usus Besar Berdasarkan Analisis Tekstur Dengan Deteksi Binary Large Object (BLOB). Bandung: Universitas Telkom; 2015.
Bala E, Ertuzun A. Applications of Multiwavelet Techniques to Image Denoising. IEEE 2002;3:581-4.
Strela V, Heller PN, Strang G, Topiwala P, Heil C. The Application of Multiwavelet Filter Banks to Image Processing. IEEE 1999;8(4):548-63.
Thomas A, Firman RN, Azhari A. Analisis radiograf periapikal menggunakan software ImageJ pada granuloma periapikal pada perawatan endodontik. Maj Kedokt Gigi Indones. 2017;3(2):105-10.
Margono G. Radiografi Periapikal Untuk Mendukung Perawatan Dalam Kedokteran Gigi. Jurnal PDGI Edisi Khusus Tahun ke-52. Jakarta: Fakultas Kedokteran Gigi Usakti; 2002.
Grossman LI, Oliet S, Del Rio CE. Ilmu Endodontik dalam Praktek, 11th ed., Prof. drg Sutatmi Suryo, Ed. Jakarta: Perpustakaan Nasional; 1995.
Garg N, Garg A. Textbook of Endodontics. New Delhi: Ajanta Offset & Packagings Ltd.; 2007. p.41.
Sitam S. Radiografi Periapikal. EGC; 2013.
Shridar B, Prasad DV. Finding 3D Teeth Positions by Using 2D Uncalibrated Dental X-Ray Images. Blenkinge Institute of Technology; 2010.
Kadir A, Susanto A. Teori dan Aplikasi Pengolahan Citra. Yogyakarta: ANDI, 2013.
Amalina N. Simulasi Matlab pada Deteksi Penyakit Gigi Granuloma Menggunakan Principal Component Analysis dan S-Transform Melalui Radiograf Periapikal dengan Metoda Radial Basis Function. Bandung: Universitas Telkom; 2014.
Utami NP. Deteksi Granuloma melalui Citra Periapikal Radiograf dengan Menggunakan Metode K-NN (K-Nearest Neighbour) pada Aplikasi Android (Skripsi). Bandung: Universitas Telkom; 2014.
Annisa A. Simulasi dan Analisis Deteksi Abses Periapikal Menggunakan Transformasi DWT (Discrete Wavelet Transform) dan metode PCA (Principal Component Analysis). Bandung: Universitas Telkom; 2014.
Gemintang RS, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal pada Deteksi Penyakit Granuloma dengan Metode Binary Large Object Berbasis Android. e-Proceeding of Engineering 2017;4(1):106-14.
Wijayanti LA, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal Pada Deteksi Penyakit Granuloma Menggunakan Metode Discrete Wavelet Transform & Principal Component Analysis Berbasis Android. e-Proceeding of Engineering 2017;4(1):333-9.
Damanik VO, Hidayat B, Sitam S. Pengolahan Citra Radiograf Periapikal Pada Deteksi Penyakit Granuloma Dengan Metode Multiwavelet Berbasis Android. e-Proceeding of Engineering 2017;4(1):547-54.
Buana QN, Hidayat B, Sitam S. Pengolahan Citra Deteksi Granuloma Melalui Periapical Radiograf Dengan Metode Transformasi Dct Dan Linier Discriminant Analysis Berbasis Android. e-Proceeding of Engineering 2017;4(1):367-71.
MATLAB Image Processing Toolbox User Guide. The Math Works Inc. 2002.
Zardi A. Klasifikasi Kanker Usus Besar Berdasarkan Analisis Tekstur Dengan Deteksi Binary Large Object (BLOB). Bandung: Universitas Telkom; 2015.
Bala E, Ertuzun A. Applications of Multiwavelet Techniques to Image Denoising. IEEE 2002;3:581-4.
Strela V, Heller PN, Strang G, Topiwala P, Heil C. The Application of Multiwavelet Filter Banks to Image Processing. IEEE 1999;8(4):548-63.
Published
2021-04-30
How to Cite
DAMAYANTI, Merry Annisa et al.
Image processing of periapical radiograph on granuloma detection by analysis method based on Android.
Jurnal Radiologi Dentomaksilofasial Indonesia (JRDI), [S.l.], v. 5, n. 1, p. 1-6, apr. 2021.
ISSN 2686-1321.
Available at: <http://jurnal.pdgi.or.id/index.php/jrdi/article/view/672>. Date accessed: 21 nov. 2024.
doi: https://doi.org/10.32793/jrdi.v5i1.672.
Section
Original Research Article
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
