A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect

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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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Vilimek, D., Kubikova, K., Kubíček, J., Barvik, D., Penhaker, M., Cerny, M., … Vondrak, J. (2020). A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12034 LNAI, pp. 90–101). Springer. https://doi.org/10.1007/978-3-030-42058-1_8

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