Deep learning for medical image processing:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
München
2023
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| Schlagworte: | |
| Online-Zugang: | Volltext Volltext |
| Beschreibung: | xvii, 174 Seiten Illustrationen, Diagramme |
| DOI: | 10.5282/edoc.33030 |
Internformat
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Datensatz im Suchindex
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| physical | xvii, 174 Seiten Illustrationen, Diagramme |
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| spelling | Rickmann, Anne-Marie 1990- Verfasser (DE-588)1316833194 aut Deep learning for medical image processing Anne-Marie Rickmann München 2023 xvii, 174 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Dissertation München, Ludwig-Maximilians-Universität 2024 3\p Bildsegmentierung (DE-588)4145448-0 gnd 4\p Kernspintomografie (DE-588)4120806-7 gnd 5\p Computertomografie (DE-588)4113240-3 gnd 6\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 7\p Bildanalyse (DE-588)4145391-8 gnd 8\p Bildverarbeitung (DE-588)4006684-8 gnd (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Online-Ausgabe urn:nbn:de:bvb:19-330303 10.5282/edoc.33030 https://doi.org/10.5282/edoc.33030 Verlag kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bvb:19-330303 Resolving-System kostenfrei Volltext 1\p emakn 0,65546 20240123 DE-101 https://d-nb.info/provenance/plan#emakn 2\p emasg 0,81908 20240123 DE-101 https://d-nb.info/provenance/plan#emasg 3\p emagnd 0,91294 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd 4\p emagnd 0,40965 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd 5\p emagnd 0,36395 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd 6\p emagnd 0,35294 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd 7\p emagnd 0,14191 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd 8\p emagnd 0,12852 20240123 DE-101 https://d-nb.info/provenance/plan#emagnd |
| spellingShingle | Rickmann, Anne-Marie 1990- Deep learning for medical image processing 3\p Bildsegmentierung (DE-588)4145448-0 gnd 4\p Kernspintomografie (DE-588)4120806-7 gnd 5\p Computertomografie (DE-588)4113240-3 gnd 6\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 7\p Bildanalyse (DE-588)4145391-8 gnd 8\p Bildverarbeitung (DE-588)4006684-8 gnd |
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| title | Deep learning for medical image processing |
| title_auth | Deep learning for medical image processing |
| title_exact_search | Deep learning for medical image processing |
| title_exact_search_txtP | Deep learning for medical image processing |
| title_full | Deep learning for medical image processing Anne-Marie Rickmann |
| title_fullStr | Deep learning for medical image processing Anne-Marie Rickmann |
| title_full_unstemmed | Deep learning for medical image processing Anne-Marie Rickmann |
| title_short | Deep learning for medical image processing |
| title_sort | deep learning for medical image processing |
| topic | 3\p Bildsegmentierung (DE-588)4145448-0 gnd 4\p Kernspintomografie (DE-588)4120806-7 gnd 5\p Computertomografie (DE-588)4113240-3 gnd 6\p Bildgebendes Verfahren (DE-588)4006617-4 gnd 7\p Bildanalyse (DE-588)4145391-8 gnd 8\p Bildverarbeitung (DE-588)4006684-8 gnd |
| topic_facet | Bildsegmentierung Kernspintomografie Computertomografie Bildgebendes Verfahren Bildanalyse Bildverarbeitung Hochschulschrift |
| url | https://doi.org/10.5282/edoc.33030 https://nbn-resolving.org/urn:nbn:de:bvb:19-330303 |
| work_keys_str_mv | AT rickmannannemarie deeplearningformedicalimageprocessing |