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Title: | The development of an appropriate setup for contrast-detail assessment of plain digital radiography systems using a CDRAD test-object |
Authors: | Abela, David (2023) |
Keywords: | Radiography, Medical -- Digital techniques Phantoms (Radiology) |
Issue Date: | 2023 |
Citation: | Abela, D. (2023). The development of an appropriate setup for contrast-detail assessment of plain digital radiography systems using a CDRAD test-object (Bachelor's dissertation). |
Abstract: | Background: The CDRAD 2.0 phantom is a radiological test-object that is a necessary aid used to test and optimise image quality by testing a detector’s low contrast and spatial resolution metrics. Objectives: The study aims to use this phantom to develop an appropriate setup for the contrast detail assessment of plain digital radiography systems. Methodology: The methodology included comparing CR with DR, copper with PMMA attenuating material and different setups with each other. Research: Excel was used to store the collected data, and Python was used to process it, make calculations and generate the relevant graphs. The CDRAD Analyser software was used to process the images obtained using the appropriate digital radiography systems. It automatically produced a Contrast Detail Group Score Diagram, a Contrast Detail Curve and a list of corresponding Image Quality Factor inverse values, which were analysed. The outcome of this study was achieved using qualitative and quantitative methods. Results: Using the Analyser’s results, it was concluded that using PMMA as an attenuating material would suffice. Conclusions and Recommendations: CDRAD 2.0 phantom is crucial at Mater Dei Hospital for its versatility and many uses. It is recommended that further research is done on the potential benefits of using an anti-scatter grid along with the final setup. |
Description: | B.Sc. (Hons)(Melit.) |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/117646 |
Appears in Collections: | Dissertations - FacHSc - 2023 Dissertations - FacSci - 2023 Dissertations - FacSciPhy - 2023 |
Files in This Item:
File | Description | Size | Format | |
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2308HSCMPH301300013881_1.PDF Restricted Access | 5.27 MB | Adobe PDF | View/Open Request a copy |
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