Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI

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Titel
Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI
verantwortlich
Meyer, Anneke (VerfasserIn); Hansen, Christian (AkademischeR BetreuerIn)
Hochschulschriftenvermerk
Dissertation, Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik, 2022
veröffentlicht
Erscheinungsjahr
2022
Erscheint auch als
Meyer, Anneke, 1990 - , Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI, Magdeburg, 2022, xiii, 169 Seiten
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E-Book Hochschulschrift
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spelling Meyer, Anneke 1990- VerfasserIn (DE-588)1268133213 (DE-627)1816709980 aut, Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI von Anneke Meyer, M.Sc., Magdeburg Universitätsbibliothek 2022, Halle (Saale) Universitäts- und Landesbibliothek Sachsen-Anhalt, 1 Online-Ressource (xiii, 167 Seiten, 28,23 MB) Illustrationen, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Literaturverzeichnis: Seite 143-169, Dissertation Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik 2022, DE-3100 Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International CC BY-SA 4.0 cc https://creativecommons.org/licenses/by-sa/4.0/, Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content, Hansen, Christian 1980- AkademischeR BetreuerIn (DE-588)138188106 (DE-627)599947543 (DE-576)306663554 dgs, Magdeburg (DE-588)4036934-1 (DE-627)104767758 (DE-576)209021322 uvp, Erscheint auch als Druck-Ausgabe Meyer, Anneke, 1990 - Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI Magdeburg, 2022 xiii, 169 Seiten (DE-627)1814220933, https://opendata.uni-halle.de//handle/1981185920/91810 Resolving-System kostenfrei, http://dx.doi.org/10.25673/89855 2022-09-07 Resolving-System kostenfrei, https://nbn-resolving.org/urn:nbn:de:gbv:ma9:1-1981185920-918106 2022-09-07 Resolving-System kostenfrei, https://d-nb.info/1266293159/34 2022-09-07 Langzeitarchivierung Nationalbibliothek kostenfrei
spellingShingle Meyer, Anneke, Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI, Hochschulschrift
title Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI
title_auth Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI
title_full Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI von Anneke Meyer, M.Sc.
title_fullStr Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI von Anneke Meyer, M.Sc.
title_full_unstemmed Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI von Anneke Meyer, M.Sc.
title_short Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI
title_sort exploiting supplementary data and knowledge for improved cnn-based segmentation of prostate structures in t2-weighted mri
title_unstemmed Exploiting supplementary data and knowledge for improved CNN-based segmentation of prostate structures in T2-weighted MRI
topic Hochschulschrift
topic_facet Hochschulschrift
url https://opendata.uni-halle.de//handle/1981185920/91810, http://dx.doi.org/10.25673/89855, https://nbn-resolving.org/urn:nbn:de:gbv:ma9:1-1981185920-918106, https://d-nb.info/1266293159/34
urn urn:nbn:de:gbv:ma9:1-1981185920-918106
work_keys_str_mv AT meyeranneke exploitingsupplementarydataandknowledgeforimprovedcnnbasedsegmentationofprostatestructuresint2weightedmri, AT hansenchristian exploitingsupplementarydataandknowledgeforimprovedcnnbasedsegmentationofprostatestructuresint2weightedmri