Abstract
Image processing plays a key role in many medical imaging applications, by automation and making delineation of regions of interest more simple. The paper describes image processing such as image properties, noise generators and edge detectors. The work deals with methods of edge detection in biomedical images using real data sets. The aim of this work are experiments providing information about the detector noise resistance. Another aim is own implementation of selected edge detection operators and an application on different types of data created by magnetic resonance imaging and computed tomography. Theoretical and experimental comparisons of edge detectors are presented.
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Acknowledgment
The work and the contributions were supported by the project SV450994/2101Biomedical Engineering Systems XV’. This study was also supported by the research project The Czech Science Foundation (GACR) 2017 No. 17-03037S Investment evaluation of medical device development run at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic. This study was supported by the research project The Czech Science Foundation (TACR) ETA No. TL01000302 Medical Devices development as an effective investment for public and private entities.
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Vilimek, D. et al. (2020). A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_8
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