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Information × Registration Number 2124U004698, Article popup.category Препринт Title popup.author Havryliv Anastasiia popup.publication 01-01-2024 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/4831 popup.publisher Description Image registration is an essential area of research in computer vision, especially medical image registration, which can find many applications in the healthcare do- main. Accurate alignment of medical data has the prospect of becoming an ex- tremely useful tool to assist medical practitioners in determining the correct diag- nosis, planning treatments, and monitoring diseases from a long-term perspective. The aim of this study is to present a comparative evaluation of the performance of the various methods for medical image registration that cover the main areas of existing algorithms’ types, including both iterative and learning-based approaches. The exploration of algorithms’ performance metrics, main advantages, and down- sides allows us to understand the possibilities of using the chosen methods for the task, which provides insights for the utilization and advancement of existing image registration techniques in clinical practice. popup.nrat_date 2025-05-09 Close