Introduction: Reliable operation of imaging equipment is the requirement for the high-quality provision of healthcare services in the field of medical imaging. Therefore, it is necessary to provide easy access and data review on quality control activities and patient dosimetry to those responsible for quality assurance. Purpose: The purpose of the master's thesis is to build an open source software solution for automating quantitative data processing that provides quality parameters of imaging equipment and exposure of patients to ionizing radiation, database storage for results, which are easily accessible to the user, data analysis of results with various graphical representations, and reporting in a standardized form for internal and external bodies that supervise quality assurance. Methods: We used open source tools (libraries) to construct and develop a system of programs that automate and connect different areas, through which we ensure standardization in the field of quality control and dosimetry. Operation of the system was assessed with retrospective study with which we compared the results of gamma camera uniformity analysis with IAEA-NMQC Toolkit and evaluated optical character recognition accuracy of CT-dose images. Uniformity was tested by comparing means. The comparison was made for every detector shape for four parameters, usually reported as uniformity results (integral and differential uniformity for UFOV and CFOV). The threshold of p-value was set at 0,05. Results: We could confirm that individual programs work as intended and that they connect and give entirety to the system. The system successfully automates the monitoring of quality control and patient radiation exposure. It also provides easy access and analysis of results with standardized reporting. Comparison of uniformity results did not show any significant statistical differences between samples (p > 0.05). The correlation of variables in each pair was strong positive (R >= 0.965) for every parameter. Discussion and conclusion: Automating data processing can effectively contribute to quality control and dosimetry activities. The most important factors to be highlighted are time efficiency and standardization.