Studi dan Pengembangan Perangkat Lunak Quality Assurance dan Quality Control Otomatis Magnetic Resonance Imaging 3 Tesla pada Fantom

Cahyana, Mohammad Sidik (2023) Studi dan Pengembangan Perangkat Lunak Quality Assurance dan Quality Control Otomatis Magnetic Resonance Imaging 3 Tesla pada Fantom. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 01111940000009-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 September 2025. Download (1MB) | Request a copy

Abstract

Magnetic Resonance Imaging (MRI) merupakan alat pencitraan medis. Citra yang dihasilkan oleh MRI perlu dilakukan Quality Assurance (QA) dan Quality Control (QC) yang rutin agar tidak mengakibatkan kesalahan diagnosa pada pasien. Penggunaan fantom sebagai objek QA/QC MRI sudah sangat lumrah digunakan dalam aplikasi klinis. Fantom memiliki kemampuan untuk dilakukan penguji kualitas pada beberapa parameter, yaitu Signal-to-Noise Ratio (SNR), Percent Image Uniformity (PIU) dan Percent Signal Ghosting (PSG). Dalam penelitian ini dikembangkan perangkat lunak berupa program untuk melakukan pengujian QA/QC secara otomatis dari citra MRI yang berkekuatan 3 T. Pengujian QA/QC secara otomatis menggunakan perangkat tersebut dibandingkan pengujian secara manual menggunakan ImageJ dapat menghemat waktu dan mengefisienkan tenaga serta menambah keakuratan dalam pengujian yang dilakukan secara berulang. Dari hasil pengujian data citra terdapat 11 dari 19 citra MRI yang diuji lolos ambang nilai minimum parameter PIU. Namun, di sisi lain seluruh data citra memiliki hasil yang baik pada parameter SNR dan PSG.
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agnetic Resonance Imaging (MRI) is a medical imaging tool. The images produced by MRI need to undergo routine Quality Assurance (QA) and Quality Control (QC) to avoid diagnostic errors in patients. The use of phantoms as QA/QC objects in MRI is a common practice in clinical applications. Phantoms have the ability to be tested for several parameters, namely Signal-to-Noise Ratio (SNR), Percent Image Uniformity (PIU), and Percent Signal Ghosting (PSG). In this research, software in the form of a program was developed to automatically perform QA/QC testing on 3T MRI images. The automated QA/QC testing using this software was compared to manual testing using ImageJ. It proved to save time, optimize resources, and improve the accuracy of repeated testing. Out of 19 tested MRI images, 11 of them passed the minimum threshold for the PIU parameter. However, all the images had good results for the SNR and PSG parameters.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Phantom, MRI, Quality Assurance, Quality Control; Fantom, MRI, Quality Assurance, Quality Control.
Subjects:	Q Science > QC Physics Q Science > QC Physics > QC271.8.C3 Calibration R Medicine > RC Internal medicine > RC78.7.N83 Magnetic resonance imaging. T Technology > T Technology (General) T Technology > T Technology (General) > T57.5 Data Processing T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.9 Signal processing.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Physics > 45201-(S1) Undergraduate Thesis
Depositing User:	Mohammad Sidik Cahyana
Date Deposited:	14 Sep 2023 02:34
Last Modified:	14 Sep 2023 02:34
URI:	http://repository.its.ac.id/id/eprint/102092

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