Image processing of periapical radiograph on granuloma detection by analysis method based on Android

  • Merry Annisa Damayanti Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132
  • Suhardjo Sitam Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132 http://orcid.org/0000-0003-0315-4884
  • Bambang Hidayat Department of Electrical Engineering, School of Electrical Engineering, Telkom University, Bandung, Indonesia 40257
  • Ivhatry Rizky Octavia Putri Susilo Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132

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.

Author Biographies

Merry Annisa Damayanti, Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132
Staff
Suhardjo Sitam, Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132
Staff
Bambang Hidayat, Department of Electrical Engineering, School of Electrical Engineering, Telkom University, Bandung, Indonesia 40257
Staff
Ivhatry Rizky Octavia Putri Susilo, Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia, 40132
Staff

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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: 28 mar. 2024. doi: https://doi.org/10.32793/jrdi.v5i1.672.

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