Efek Penggunaan Compressed Sensing Magnetic Resonance Imaging Hasil Rekonstruksi Pada Signal to Noise Ratio Citra Brachial Plexus dan Fantom CS MATLAB

Humairo, Luthfia (2024) Efek Penggunaan Compressed Sensing Magnetic Resonance Imaging Hasil Rekonstruksi Pada Signal to Noise Ratio Citra Brachial Plexus dan Fantom CS MATLAB. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Magnetic Resonance Imaging (MRI) adalah teknik pencitraan medis non invasif dengan menggunakan medan magnet sebagai komponen utama. Hasil citra MRI menunjukkan bidang atau irisan bagian dalam tubuh manusia. Kualitas citra MRI yang optimal salah satunya ditentukan oleh signal to noise ratio (SNR). SNR sangat berpengaruh terhadap kualitas citra, peningkatan nilai SNR diikuti dengan peningkatan kualitas citra. Penggunaan teknik compressed sensing pada pencitraan MRI menawarkan banyak keuntungan, terutama dalam hal efisiensi dan kenyamanan pasien. Pada penelitian ini penulis menggunakan sampel, yaitu pleksus brakialis dan fantom CS MATLAB. Berdasarkan hasil nilai SNR yang diperoleh dari masing-masing sampel yang telah diolah menggunakan microsoft excel. Dengan teknik compressed sensing dalam MRI dapat mempercepat proses scanning tanpa mengurangi kualitas citra dan waktu pemindaian.
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Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique using a magnetic field as the main component. The results of MRI images show planes or slices of the inside of the human body. The optimal quality of MRI images is determined by the signal to noise ratio (SNR). SNR has a big influence on image quality, increasing the SNR value is followed by increasing image quality. The use of compressed sensing techniques in MRI imaging offers many advantages, especially in terms of efficiency and patient comfort. In this research, the author used samples, namely Brachial Plexus and Phantom CS MATLAB. Based on the results of the SNR values obtained from each sample that has been processed using Microsoft Excel. Using compressed sensing techniques in MRI can speed up the scanning process without reducing image quality and scanning time.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Compressed sensing, Fantom CS MATLAB, MRI, Pleksus Brakialis, Signal to noise ratio, Brachial Plexus, Compressed Sensing, Phantom CS MATLAB, Signal to noise ratio
Subjects:	Q Science > QA Mathematics > QA404 Fourier series Q Science > QA Mathematics > QA611.28 Metric spaces Q Science > QA Mathematics > QA76.6 Computer programming. Q Science > QC Physics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Physics > 45201-(S1) Undergraduate Thesis
Depositing User:	Luthfia Humairo
Date Deposited:	14 Aug 2024 08:04
Last Modified:	14 Aug 2024 08:04
URI:	http://repository.its.ac.id/id/eprint/114400

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