izpis_h1_title_alt

Določanje kakovosti ultrazvočne opreme z merjenjem razmerja signal - šum na ultrazvočnih slikah : magistrsko delo
ID Vodopivec, Tine (Author), ID Žibert, Janez (Mentor) More about this mentor... This link opens in a new window, ID Arnuga, Sašo (Co-mentor), ID Fošnarič, Miha (Reviewer)

.pdfPDF - Presentation file, Download (2,34 MB)
MD5: BB9B1DEDE80ADFB7658C33A7F45B89F2

Abstract
Uvod: Ultrazvok je napredna tehnologija na področju intervencijskega preverjanja bolečin. Kontrola kvalitete je nepogrešljiva za zagotavljanje kvalitete slik in natančnosti aparata. V ultrazvočni diagnostiki lahko merimo in kontroliramo različne parametre, kot sta razmerji signal – šum (SNR) za merjenje občutljivosti slikovnega sistema in kontrast – šum (CNR) za ovrednotenje upadanja kontrasta na sliki. Namen: Namen magistrske naloge je razviti aplikacijo, s pomočjo katere bomo lahko merili razmerje signal – šum na ultrazvočnih slikah. V drugem delu raziskovalne naloge bomo ob uporabi aplikacije preverjali, kako se parametra SNR in CNR spreminjata pri različnih globinah merjenja, različnih ojačitvah signala (angl. gain) ter različnih frekvencah. Metode dela: Pri izdelavi magistrske naloge smo uporabili deskriptivno metodo s pregledom domače in tuje literature ter eksperimentalno metodo za izdelavo aplikacije, njeno primerjavo z že obstoječim programom za obdelavo slik FIJI ImageJ ter samo merjenje parametrov kakovosti na ultrazvočnih slikah. Aplikacijo smo zasnovali v programskem jeziku Python, različica 3.6, in sicer smo si pri tem pomagali z računalniškim programom Visual Studio Code. Rezultati: Pri vsakem izmed treh tipov fantoma smo naredili več ultrazvočnih posnetkov z različnima sondama. Z vsemi štirimi opravljenimi Wilcoxonovimi testi predznaka smo odkrili, da so meritve naše aplikacije primerljive z meritvami programa FIJI. Drugi del eksperimenta smo razdelili na tri dele, in sicer: 1. vpliv frekvence signala na SNR in CNR, 2. vpliv ojačitve signala na SNR in CNR in 3. vpliv globine merjenja na SNR in CNR. Razprava in zaključek: Ob primerjavi izdelane aplikacije z uveljavljenim programom na področju analize medicinskih slik FIJI ImageJ smo ugotovili, da pri računanju parametrov SNR in CNR ne prihaja do statistično značilnih odstopanj. Z eksperimentom smo dokazali, da potrebujemo pri izvajanju kontrole kakovosti ob računanju razmerja signal – šum tudi izračun parametra kontrast – šum, saj je lahko slika kljub odličnemu razmerju SNR še vedno diagnostično neuporabna, če na njej zaradi slabega kontrasta med seboj ne ločimo dveh sosednjih struktur.

Language:Slovenian
Keywords:magistrska dela, radiološka tehnologija, ultrazvok, kontrola kakovosti, razmerje signal – šum, razmerje kontrast – šum
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:ZF - Faculty of Health Sciences
Place of publishing:Ljubljana
Publisher:[T. Vodopivec]
Year:2022
Number of pages:52 str.
PID:20.500.12556/RUL-145141 This link opens in a new window
UDC:616-07
COBISS.SI-ID:148323331 This link opens in a new window
Publication date in RUL:08.04.2023
Views:536
Downloads:130
Metadata:XML RDF-CHPDL DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Title:Ultrasound quality assurance with signal-to-noise ratio on ultrasound images : master thesis
Abstract:
Introduction: Ultrasound is an advanced technology in the field of interventional pain screening. Quality control is indispensable to ensure the quality of the images and the accuracy of the device. In diagnostic ultrasound, various parameters can be measured and controlled, such as signal-to-noise ratio (SNR), used to determine the sensitivity of the imaging system and contrast-to-noise ratio (CNR), which is used to evaluate the contrast decay and is an estimate of the noise present in the image. Purpose: The purpose of this master thesis is to develop an application that can be used to measure the signal-to-noise ratio in ultrasound images. In the second part of the thesis, we will use the application to test how the SNR and CNR parameters change at different measurement depths, different gain and different frequencies. Methods: In the process of making this master thesis, descriptive and experimental methods were used. The application was designed in the Python programming language, version 3.6, using Visual Studio Code. Results: For each of the three phantom types, we took several images with the two probes. With all four Wilcoxon signed-rank tests performed, we found that the measurements of our application are comparable to those of FIJI. The second part of the experiment was divided into three parts, namely: 1. the influence of the frequency on SNR and CNR, 2. the influence of the gain on SNR and CNR, and 3. the influence of the measurement depth on SNR and CNR. Discussion and Conclusion: Comparing the developed application with the well-established FIJI ImageJ medical image analysis software, we found that there are no statistically significant deviations in the calculation of SNR and CNR parameters. We have shown experimentally that when performing quality control, we need to calculate the contrast-to-noise parameter in addition to the signal-to-noise ratio, because even if an image has an excellent SNR, it may still be diagnostically unusable if two adjacent structures in the image are not distinguishable from each other due to poor contrast.

Keywords:master's theses, radiologic technology, ultrasound, quality assurance, signal to noise ratio, contrast to noise ratio

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back