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UTILIZING ALGORITHMS FOR IMAGING MEDICAL RESULTS FROM CT, MRI, AND PET INTO VIRTUAL REALITY
Abstract
Utilizing algorithms for imaging medical results from CT, MRI, and PET into Virtual Reality. There is a growing interest in the field of medical imaging in understanding the impact of algorithm parameters on the quality and interpretability of the obtained images. In the developed software VRMed3D aimed at educating students using medical images in virtual reality technology, Gaussian noise was utilized to identify the most effective edge detection algorithms. The search was for an algorithm that provided the most optimal quality of generated images while maintaining the shortest possible waiting time. The aim of this study is to present the results of tests on the impact of changing input parameters of algorithms on the outcome. The article discusses the current state of research, then describes the conducted analysis of algorithms: Gaussian noise, grouping neighboring illumination values, noise removal, and edge detection. Finally, the effects of algorithm configurations on the final outcome are discussed.
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