Abstract
Psychovisual experiments support the notion that a considerable amount of information is contained in region boundaries such as edges and linear features [1]. Thus, as long as these elements are preserved, it is possible to simplify images drastically with no apparent loss of content. Linear features also underlie the organization of many structures of interest in biology, remote sensing, medicine, and engineering. Examples include rivers and their deltas, road networks, the circulatory system, and textile microstructure (see [2] for a more extensive list and Chapters 6, 7, and 11 in this book).
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Acknowledgements
The authors would like to thank the following people for allowing us to use their images as sample images: Marjo Götte, Novartis Institutes for BioMedical Research; Dr. Myles Fennell, Wyeth Research, Princeton, NJ, USA; Dr. Xiaokui Zhang, Helicon Therapeutics, Inc., USA; Prof. Pat Doherty, Kings College, London, UK; Dr. Jenny Gunnersen, Prof. Seong-Seng Tan, and Dr. Ross O’Shea Howard Florey Institute, Melbourne; Ass. Prof. Cynthia Whitchurch, UTS, Sydney.
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Domanski, L. et al. (2011). High-Throughput Detection of Linear Features: Selected Applications in Biological Imaging. In: Dougherty, G. (eds) Medical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9779-1_8
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DOI: https://doi.org/10.1007/978-1-4419-9779-1_8
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