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Efektivitas Algoritma Selective Mean Filter Untuk Mengurangi Noise Pada Citra Fluoroscopy

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ABSTRAK
Penelitian ini bertujuan untuk mengimplementasikan algoritma pengurangan noise
dengan Selective mean filter (SMF) dan untuk menyelidiki waktu komputasi dalam
proses denoising pada citra – citra sinar-X fluoroscopy. SMF adalah teknik mean
filter (MF), tetapi dalam aplikasinya, hanya piksel dalam nilai ambang yang
digunakan untuk menghitung nilai piksel rata-rata. Keefektifan SMF kemudian
dibandingkan dengan filter sudah dikenal, seperti adaptive mean filter (AMF) dan
bilateral filter (BF). Pengolahan citra menggunakan komputer Acer Nitro 5 Intel
Core i5-8300H 2.3 GHz dengan RAM 8GB, Grafic Processor Units (GPU) Nvidia
Geforce GTX 1050 4GB, dan sistem operasi Windows 10 Home dengan SSD M.2
NVMe 2280 256GB. Algoritma diimplementasikan menggunakan Matlab R2019b.
Citra – citra fluoroscopy dari fantom NEMA SCA & I Cardiovascular Fluoroscopic
Benchmark dengan ukuran 512 x 512 piksel dilakukan filtering, faktor paparan low,
normal, dan high pada mode 15 FPS dan 30 FPS dengan field of view ( FOV) 25
cm. Selain itu, kualitas citra yang telah difilter dinilai, termasuk tingkat noise, rasio
signal-to-noise (SNR), rasio contrast-to-noise (CNR), dan resolusi spasial. Hasil
penelitian menunjukkan bahwa dengan menggunakan SMF didapatkan
peningkatan kualitas citra dalam hal tingkat noise, SNR, CNR, dan resolusi spasial
dibandingkan dengan AMF dan BF. Waktu yang dibutuhkan oleh SMF untuk
memproses citra adalah 0,36 detik, sedangkan AMF dan BF masing-masing 10,6
dan 1,4 detik.
Kata kunci: Selective mean filter, pengurangan noise, fluoroscopy, kardiovaskular

ABSTRACT
This study aims to implement noise reduction algorithm with a Selective mean filter
(SMF) and to investigate its computation time in the denoising process on X-ray
fluoroscopy images. The SMF was the mean filter (MF) technique, but in its
application, Selective pixels within threshold value were only used to calculate the
average pixel value. The effectiveness of SMF was then compared to well-known
filters, such as adaptive mean filter (AMF) and bilateral filter (BF). The notebook
of Acer Nitro 5 Intel Core i5-8300H 2.3 GHz with 8GB RAM, Graphic Processor
Unit (GPU) Nvidia Geforce GTX 1050 4GB, and the Windows 10 Home operating
system with SSD M.2 NVMe 2280 256GB were utilized. The algorithm was
implemented using Matlab R2019b. The fluoroscopy images of NEMA SCA & I
Cardiovascular Fluoroscopic Benchmark Phantom with size of 512 x 512 pixels
were filtered, exposure factors of low, normal, high for 15 FPS and 30 FPS with a
field of view (FOV) of 25 cm. In addition, image quality of the filtered images was
assessed, including noise level, signal-to-noise ratio (SNR), contrast-to-noise ratio
(CNR), and spatial resolution. The results showed that by using the SMF, the higher
improvement of image quality in terms of noise level, SNR, CNR, and spatial
resolution compared to AMF and BF, was achieved. The time needed by SMF to
process an image was about 0.36 seconds, while the AMF and BF are 10.6 and 1.4
seconds, respectively.
Keywords: Selective mean filter, noise reduction, fluoroscopy, cardiovascular

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Ketersediaan

079S2FIS20IV

079 S2FIS 20-iv

Perpustakaan FSM Undip (Referensi)

Tersedia

Informasi Detail

Judul Seri

MAGISTER FISIKA

No. Panggil

079 S2FIS 20-iv

Penerbit

: ., 2020

Deskripsi Fisik

-

Bahasa

Indonesia

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

-

Info Detail Spesifik

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Pernyataan Tanggungjawab

Jhon Hadearon Saragih

Versi lain/terkait

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