Evaluasi Teknik Filtering Contrast Enhancement dan Edge Sharpening untuk Pengolahan Citra Ultrasonografi Prostat

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Published: Jun 21, 2021
DOI: https://doi.org/10.47313/jig.v24i1.1076

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Ni Larasati Kartika Sari
Fisika, Universitas Nasional
Ryscha Dwi Iriani
Program Studi Fisika, Universitas Nasional, Jakarta
Erna Yunika
Program Studi Fisika, Universitas Nasional, Jakarta
Budi Santoso
Program Studi Fisika, Universitas Nasional, Jakarta

Abstract

One of the modality to detect prostate’s abnormalities is ultrasonography (USG). Indonesia still relies on 2D USG images despite its weaknesses. In this research, image processing called Computer-Aided Diagnostic (CAD) was performed on 2D USG prostate images. This research is a basic CAD research to improve the quality of 2D USG images with various combination of image procesing methods. Evaluation of the processed images are performed by not only SNR method, but also evaluation from clinicians. Twenty prostate images were used with normal and abnormal diagnosis. Image processing methods used are median filter, wiener filter, gaussian filter, CLAHE (Contrast Limited Adaptive Histogram Equalization) contrast enhancement and image sharpening. Those methods were combined so there are three combinations to be evaluated. Among 3 combinations, gaussian filter combination has the highest SNR in normal and abnormal images. But, qualitative evaluation performed by clinicians shows that median filter combination has the best visualization of prostate capsule and prostate size. Evaluation from comparing pixel value and prostate size between normal and abnornal images shows that median filter combination has the biggest differences, 13.11, makes it the best combinaton to show different visualization of normal and abnormal prostate.

Article Details

How to Cite
Kartika Sari, N. L., Iriani, R. D., Yunika, E., & Santoso, B. (2021). Evaluasi Teknik Filtering Contrast Enhancement dan Edge Sharpening untuk Pengolahan Citra Ultrasonografi Prostat. Jurnal Ilmiah Giga, 24(1), 1–8. https://doi.org/10.47313/jig.v24i1.1076
Issue
Vol. 24 No. 1 (2021): Volume 24 Edisi 1 Tahun 2021
Section
Articles

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