Establishment of a guided, in vivo, multi-channel, abdominal, tissue imaging approach

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Bahlmann, J.; Madrahimov, N.; Daniel, F.; Theidel, D.; DeTemple, D.E. et al.: Establishment of a guided, in vivo, multi-channel, abdominal, tissue imaging approach. In: Scientific Reports 10 (2020), Nr. 1, 9224. DOI: https://doi.org/10.1038/s41598-020-65950-w

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Sum total of downloads: 94




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Abstract: 
Novel tools in humane animal research should benefit the animal as well as the experimentally obtained data. Imaging technologies have proven to be versatile and also in accordance with the demands of the 3 R principle. However, most imaging technologies are either limited by the target organs, number of repetitive imaging sessions, or the maximal resolution. We present a technique-, which enables multicolor abdominal imaging on a tissue level. It is based on a small imaging fiber endoscope, which is guided by a second commercial endoscope. The imaging fiber endoscope allows the distinction of four different fluorescence channels. It has a size of less than 1 mm and can approximately resolve single cells. The imaging fiber was successfully tested on cells in vitro, excised organ tissue, and in mice in vivo. Combined with neural networks for image restauration, high quality images from various abdominal organs of interest were realized. The second endoscope ensured a precise placement of the imaging fiber in vivo. Our approach of guided tissue imaging in vivo, combined with neuronal networks for image restauration, permits the acquisition of fluorescence-microscope like images with minimal invasive surgery in vivo. Therefore, it is possible to extend our approach to repetitive imaging sessions. The cost below 30 thousand euros allows an establishment of this approach in various scenarios. © 2020, The Author(s).
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Mathematik und Physik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 49 52.13%
2 image of flag of United States United States 21 22.34%
3 image of flag of China China 7 7.45%
4 image of flag of Czech Republic Czech Republic 5 5.32%
5 image of flag of No geo information available No geo information available 4 4.26%
6 image of flag of Ukraine Ukraine 1 1.06%
7 image of flag of Taiwan Taiwan 1 1.06%
8 image of flag of Romania Romania 1 1.06%
9 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 1.06%
10 image of flag of Greece Greece 1 1.06%
    other countries 3 3.19%

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