Aplikasi Image Enhancement untuk Peningkatan Kualitas Citra Ultrasonografi Ginjal


  • Ni Larasati Kartika Sari Fisika, Universitas Nasional
  • Inti Ermina Br Barus Universitas Nasional
  • Budi Santoso Universitas Nasional
  • Dewi Muliyati
  • Purwantiningsih Purwantiningsih Universitas Nasional
  • Idris Kusuma Universitas Nasional




average filter, gausian filter, median filter, wiener filter, contrast enhancement, image sharpening.


Abstract. Combination of four filters namely gaussian filter, median filter, wiener filter, average filter were tested using two contrast enhancement techniques, intensity adjustment and histogram equalization, were tested to improve the quality of kidney ultrasound images. The research was conducted using 40 images, consist of 9 normal images, 17 hydronerfosis images, and 14 kidney stones images. The measured image quality were PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error). The higher the PSNR and the lower the MSE, the better the image quality. Visual evaluation through questionnaires to clinicians has also been carried out to assess the visualization of the kidney and its abnormalities. The results of PSNR and MSE calculations showed that every image processings methods combinations produce different results in each image categories. However, whether in normal, hydronefrosis, or kindey stone categories, the combination of filters with image adjustment method gave the highest PSNR and lowest MSE. Meanwhile, the results of the visual evaluation from the clinicians showed that the best image enhancement technique in improving the visualization of abnormalities in kidney ultrasound images (Hydronephrosis and kidney stones) was the combination of a wiener filter with intensity adjustment, in accordance with the results of the PSNR measurement.

Abstrak.  Telah diuji kombinasi empat metode filter yaitu gaussian filter, median filter, wiener filter dan average filter dengan peningkatan kontras, intensity adjustment dan histogram equalization untuk meningkatkan kualitas citra ultrasonografi ginjal. Penelitian dilakukan dengan menggunakan 40 citra, dengan rincian 9 citra normal, 17 citra Hydronerfosis, dan 14 citra batu ginjal. Kualitas citra yang diukur adalah PSNR dan MSE. Evaluasi visual melalui kuesioner terhadap klinisi juga telah dilakukan. Untuk citra normal, nilai PSNR tertinggi, yaitu 14.21 dan MSE  terendah, yaitu 2.62 diperoleh pada kombinasi median filter dengan intensity adjustment. Untuk citra hydronefrosis, PSNR tertinggi diperoleh pada kombinasi wiener filter dengan intensity adjustment, yaitu 4.42 dan nilai MSE terendah diperoleh pada kombinasi average filter dengan intensity adjustment, yaitu 3.37. Pada citra batu ginjal, nilai PSNR tertinggi diperoleh pada kombinasi wiener filter dengan intensity adjustment, yaitu 15.48, serta nilai MSE terendah merupakan kombinasi gaussian filter dengan intensity adjustment, yaitu 3.23. Sementara itu, hasil evaluasi visual dari dokter klinisi menunjukkan bahwa teknik image enhancement yang paling baik dalam meningkatkan visualisasi abnormalitas pada citra USG ginjal hydronefrosis dan batu ginjal adalah merupakan kombinasi wiener filter dengan  intensity adjustment, sesuai dengan hasil pengukuran PSNR.


Y. Mohamed, Y. Abdallah, A. S. Algaddal, and M. A. Alkhir, “Enrichment of Ultrasound Images using Contrast Enhancement Techniques Segmentation of human organs using image processing technique View project Medical Image processing View project Enrichment of Ultrasound Images using Contrast Enhancement Techniques,” 2013. [Online]. Available: www.ijsr.net

Priyanka and D. Kumar, “Feature Extraction and Selection of kidney Ultrasound Images Using GLCM and PCA,” in Procedia Computer Science, 2020, vol. 167, pp. 1722–1731. doi: 10.1016/j.procs.2020.03.382.

S. F. Huang, R. F. Chang, D. R. Chen, and W. K. Moon, “Characterization of Spiculation on Ultrasound Lesions,” IEEE Transactions on Medical Imaging, vol. 23, no. 1, pp. 111–121, Jan. 2004, doi: 10.1109/TMI.2003.819918.

J. J. Cerrolaza, N. Safdar, C. A. Peters, E. Myers, J. Jago, and M. G. Linguraru, “Segmentation of kidney in 3D-ultrasound images using gabor-based appearance models,” in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Jul. 2014, pp. 633–636. doi: 10.1109/isbi.2014.6867950.

J. C. Bamber and C. Daft, “Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images.”, Ultrasonics. January 1986

T. Loupas, W. N. Mcdicken, and P. L. Allan, An Adaptive Weighted Median Filter for Speckle Suppression in Medical Ultrasonic Images, IEEE Transactions On Circuits And Systems, VOL. 36, NO. 1, JANUARY 1989

S. Sudha, G. R. Suresh, and R. Sukanesh, “Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance,” International Journal of Computer Theory and Engineering, pp. 7–12, 2009, doi: 10.7763/ijcte.2009.v1.2.

N. Larasati, K. Sari, R. Dwi Iriani, E. Yunika, and B. Santoso, “Evaluasi Teknik Filtering Contrast Enhancement dan Edge Sharpening untuk Pengolahan Citra Ultrasonografi Prostat,” Jurnal Ilmiah GIGA, vol. 24, no. 1, pp. 2021–2022, doi: 10.47313/jig.v%vi%i.1076.

N. L. Kartika Sari, R. D. Iriani, and B. Santoso, “Pengolahan Citra untuk Meningkatkan Visualisasi Lesi Jinak Citra USG Payudara,” Jurnal Ilmiah Giga, vol. 23, no. 2, p. 76, Nov. 2020, doi: 10.47313/jig.v23i2.935.

K. Hansen, M. Nielsen, and C. Ewertsen, “Ultrasonography of the Kidney: A Pictorial Review,” Diagnostics, vol. 6, no. 1, p. 2, Dec. 2015, doi: 10.3390/diagnostics6010002.

A. A. Sanusi et al., “Relationship of ultrasonographically determined kidney volume with measured GFR, calculated creatinine clearance and other parameters in chronic kidney disease (CKD),” Nephrology Dialysis Transplantation, vol. 24, no. 5, pp. 1690–1694, May 2009, doi: 10.1093/ndt/gfp055.

Budi, U. Fahnun, A Benny Mutiara, J. Harlan, Eri, and P. Wibowo, “Feature Identification of Hepatic Cancer Ultrasound Image using Gaussian Filtering Combined with Intensity Adjustment.” International Journal of Engineering Research & Technology (IJERT), Vol. 8 Issue 09, September-2019

R. Munir, “Pengantar Pengolahan Citra IF4073 Interpretasi dan Pengolahan Citra,” 2019.

H. Kareem, R. Husain AAli, and G. AHafedh Jaber, “Noise Removed by Processing the Lightness and Chromatic Components Basic on YC b C r Color Space., Journal of Babylon University/Pure and Applied Sciences/ No.(9)/ Vol.(24): 2016

L. Şendur and I. W. Selesnick, “Bivariate shrinkage with local variance estimation,” IEEE Signal Processing Letters, vol. 9, no. 12. pp. 438–441, Dec. 2002. doi: 10.1109/LSP.2002.806054.