Efektivitas Nilai PSNR dan Informasi Citra terhadap Kombinasi Teknik Bilateral Filter dan Non-Local Means sebagai Denoising pada Verifikasi Radioterapi Regio Pelvis

Nyoman Indah Sukmasari, Gatot Murti Wibowo, Bagus Dwi Handoko, Bedjo Santoso, Siti Masrochah

Sari


ABSTRACT

 

The quality of radiotherapy verification images on a 6 MeV Linear Accelerator (Linac) often decreases due to noise generated by high energy, potentially reducing the accuracy of irradiation positioning and endangering surrounding healthy tissues. The combination of Bilateral Filter and Non-Local Means techniques is a denoising method designed to reduce noise while preserving important image details. This study aims to evaluate the effectiveness of combining these two techniques in improving the quality of pelvis region verification images, focusing on the quantitative parameter Peak Signal-to-Noise Ratio (PSNR) and the qualitative parameter of image information. The research design used was Research and Development (R&D) with 20 samples of anteroposterior (AP) and lateral projection verification images obtained from the Electronic Portal Imaging Device (EPID) of a 6 MeV Linac at the Radiotherapy Unit of RSUD Dr. Moewardi. The denoising process was performed using Python–OpenCV. PSNR values were measured before and after denoising, while image information was assessed by four expert evaluators using a 1–5 scale checklist. Statistical analysis employed paired t-test or Wilcoxon test for PSNR, and Wilcoxon test as well as Cohen’s Kappa for image information. The results showed a significant increase in PSNR values in both projections (p < 0.05) with an N-gain score of 59%–64%. Image information assessment also showed a significant improvement (p < 0.05), with Cohen’s Kappa indicating moderate to strong agreement among evaluators. Therefore, the combination of Bilateral Filter and Non-Local Means has been proven effective in improving the quality of pelvis region radiotherapy verification images, potentially enhancing irradiation accuracy and patient safety.

 

Keywords: PSNR, Bilateral Filter, Non Local Means, Radiotherapy.

 

 

ABSTRAK

 

Kualitas citra verifikasi radioterapi pada Linear Accelerator (Linac) 6 MeV sering menurun akibat noise yang dihasilkan oleh energi tinggi, sehingga berpotensi mengurangi akurasi penentuan posisi penyinaran dan membahayakan jaringan sehat di sekitarnya. Kombinasi teknik Bilateral Filter dan Non-Local Means merupakan metode denoising yang dirancang untuk mengurangi noise sekaligus mempertahankan detail penting citra. Penelitian ini bertujuan mengevaluasi efektivitas kombinasi kedua teknik tersebut dalam meningkatkan kualitas citra verifikasi regio pelvis, dengan fokus pada parameter kuantitatif Peak Signal to Noise Ratio (PSNR) dan parameter kualitatif informasi citra. Desain penelitian yang digunakan Adalah Research and Development (RnD) dengan 20 sampel citra verifikasi proyeksi AP dan lateral yang diambil dari Electronic Portal Imaging Device (EPID) Linac 6 MeV di Instalasi Radioterapi RSUD Dr. Moewardi. Proses denoising dilakukan menggunakan Python–OpenCV. Nilai PSNR diukur sebelum dan sesudah denoising, sedangkan informasi citra dinilai oleh empat penilai ahli menggunakan lembar checklist skala 1–5. Analisis statistik menggunakan uji paired t-test atau Wilcoxon untuk PSNR, dan uji Wilcoxon serta Cohen’s Kappa untuk informasi citra. Hasil penelitian menunjukkan adanya peningkatan signifikan nilai PSNR pada kedua proyeksi (p<0,05) dengan N-gain skor 59%–64%. Penilaian informasi citra juga meningkat signifikan (p<0,05), dengan nilai Cohen’s Kappa menunjukkan kesepakatan moderat hingga kuat antar penilai. Dengan demikian, kombinasi Bilateral Filter dan Non-Local Means terbukti efektif meningkatkan kualitas citra verifikasi radioterapi regio pelvis, yang berpotensi meningkatkan akurasi penyinaran dan keselamatan pasien.

 

Kata Kunci: PSNR, Bilateral Filter, Non Local Means, Radioterapi.


Teks Lengkap:

Download Artikel

Referensi


Al-Hallaq, H. A., Chmura, S. J., Salama, J. K., Winter, K. A., & Robinson, C. G. (2018). Clinical Implementation Of Image-Guided Radiotherapy: Lessons Learned From The Nrg Oncology Clinical Trials. International Journal Of Radiation Oncology, Biology, Physics, 101(4), 945–956. Https://Doi.Org/10.1016/J.Ijrobp.2018.03.039

Amin, M. B., Edge, S. B., Greene, F. L., Byrd, D. R., Brookland, R. K., Washington, M. K., ... & Madera, M. (2018). Ajcc Cancer Staging Manual (8th Ed.). Springer.

Baskar, R., Lee, K. A., Yeo, R., & Yeoh, K. W. (2019). Cancer And Radiation Therapy: Current Advances And Future Directions. International Journal Of Medical Sciences, 19(3), 526–542. Https://Doi.Org/10.7150/Ijms.20227

Gupta, T., Master, Z., Kannan, S., Agarwal, J. P., Ghose, A., & Budrukkar, A. (2022). Observer Variability In Image Interpretation: Impact Of Training And Experience On Diagnostic Performance. Radiotherapy And Oncology, 170, 76–83. Https://Doi.Org/10.1016/J.Radonc.2022.04.008

Hayati, A. (2023). Penggunaan N-Gain Untuk Evaluasi Efektivitas Pembelajaran. Jurnal Pendidikan Dan Evaluasi, 14(2), 45–53.

Huang, T., Bai, L., & Wu, Y. (2016). Edge-Preserving Image Denoising Using Bilateral Filter With Texture Feature. Journal Of Visual Communication And Image Representation, 41, 80–91. Https://Doi.Org/10.1016/J.Jvcir.2016.08.006

International Agency For Research On Cancer (Iarc). (2023). Global Cancer Observatory: Cancer Today. Https://Gco.Iarc.Fr/Today

Juliasa, D. (2020). Analisis Kualitas Citra Radiografi Digital Menggunakan Parameter Psnr Dan Ssim. Jurnal Teknologi Kesehatan, 9(1), 12–20.

Lee, H. J., Park, S. Y., Kim, S., & Lee, K. H. (2023). Quantitative Assessment Of Image Quality Using Psnr And Ssim In Medical Imaging. Medical Physics, 50(2), 123–133. Https://Doi.Org/10.1002/Mp.16000

Mundanti, R. (2023). Efektivitas Metode Pembelajaran Berbasis Proyek Ditinjau Dari N-Gain. Jurnal Inovasi Pendidikan, 11(1), 33–40.

Nguyen, D., Kang, M., & Park, S. (2020). Noise Reduction In Portal Imaging For Radiotherapy Verification. Physics In Medicine & Biology, 65(12), 125007. Https://Doi.Org/10.1088/1361-6560/Ab8c4e

Radhika, P. (2023). Enhancement Of Medical Images Using Hybrid Bilateral And Non-Local Means Filter. Biomedical Engineering Advances, 5, 100076. Https://Doi.Org/10.1016/J.Bea.2023.100076

Sara, N., Putri, D., & Rahman, A. (2019). Evaluasi Kualitas Citra Medis Menggunakan Psnr Dan Ssim. Jurnal Teknologi Informasi Kesehatan, 11(2), 45–52.

Singh, A., Kumar, V., & Kaur, P. (2020). Anatomical Landmark Detection For Pelvic Radiotherapy Verification. Journal Of Medical Imaging And Radiation Oncology, 64(5), 712–720. Https://Doi.Org/10.1111/1754-9485.13041

Van Elmpt, W., Mcdermott, L. N., Nijsten, S., Wendling, M., Lambin, P., & Mijnheer, B. (2015). A Literature Review Of Electronic Portal Imaging For Radiotherapy Dosimetry. Radiotherapy And Oncology, 115(2), 215–229. Https://Doi.Org/10.1016/J.Radonc.2015.05.016

Wang, Y., Sun, J., & Chen, Z. (2021). Image Denoising Based On Improved Non-Local Means Algorithm For Medical Imaging. Biomedical Signal Processing And Control, 63, 102157. Https://Doi.Org/10.1016/J.Bspc.2020.102157

World Health Organization (Who). (2023). Cancer Fact Sheet. Https://Www.Who.Int/News-Room/Fact-Sheets/Detail/Cancer

Zhang, X., Li, H., & Zhou, Y. (2017). Image Quality Assessment Based On Psnr For Medical Image Denoising. Journal Of Digital Imaging, 30(4), 487–495. Https://Doi.Org/10.1007/S10278-017-9993-6

Zhang, Y. (2025). Comparative Analysis Of Denoising Algorithms For Radiotherapy Imaging. Journal Of Medical Imaging Research, 14(1), 55–67. Https://Doi.Org/10.1002/Jmir.2567




DOI: https://doi.org/10.33024/mahesa.v6i4.22131

Refbacks

  • Saat ini tidak ada refbacks.


Publisher: Universitas Malahayati Lampung

Creative Commons License
Semua artikel dapat digunakan dibawah lisensi Creative Commons Attribution-ShareAlike 4.0 International License