Status: Bibliographieeintrag
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| |  Online-Ressource |
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| Verfasst von: | Chen, Shuqing [VerfasserIn]  |
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| | Zhong, Xia [VerfasserIn] |
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| | Hu, Shiyang [VerfasserIn] |
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| | Dorn, Sabrina [VerfasserIn] |
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| | Kachelrieß, Marc [VerfasserIn] |
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| | Lell, Michael [VerfasserIn] |
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| | Maier, Andreas [VerfasserIn] |
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| Titel: | Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks |
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| Verf.angabe: | Shuqing Chen, Xia Zhong, Shiyang Hu, Sabrina Dorn, Marc Kachelrieß, Michael Lell, Andreas Maier |
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| E-Jahr: | 2020 |
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| Jahr: | 1 January 2020 |
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| Umfang: | 11 S. |
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| Fussnoten: | Gesehen am 31.03.2020 |
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| Titel Quelle: | Enthalten in: Medical physics |
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| Ort Quelle: | Hoboken, NJ : Wiley, 1974 |
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| Jahr Quelle: | 2020 |
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| Band/Heft Quelle: | 47(2020), 2, Seite 552-562 |
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| ISSN Quelle: | 2473-4209 |
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| | 1522-8541 |
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| Abstract: | Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissues compared to conventional single-energy CT (SECT). Recent research shows that automatic multi-organ segmentation of DECT data can improve DECT clinical applications. However, most segmentation methods are designed for SECT, while DECT has been significantly less pronounced in research. Therefore, a novel approach is required that is able to take full advantage of the extra information provided by DECT. |
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| DOI: | doi:10.1002/mp.13950 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext ; Verlag: https://doi.org/10.1002/mp.13950 |
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| | Volltext: https://aapm.onlinelibrary.wiley.com/doi/abs/10.1002/mp.13950 |
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| | DOI: https://doi.org/10.1002/mp.13950 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | DECT |
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| | deep learning |
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| | FCN |
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| | multi-organ |
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| | U-Net |
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| K10plus-PPN: | 1693629631 |
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| Verknüpfungen: | → Zeitschrift |
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Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks / Chen, Shuqing [VerfasserIn]; 1 January 2020 (Online-Ressource)
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