Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study
We aimed to develop a framework relying on artificial neural networks (ANNs) for fully automated quantitative analysis of MRI in neuro-oncology to overcome the inherent limitations of manual assessment of tumour burden.
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
April 2, 2019
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| In: |
The lancet. Oncology
Year: 2019, Jahrgang: 20, Heft: 5, Pages: 728-740 |
| ISSN: | 1474-5488 |
| DOI: | 10.1016/S1470-2045(19)30098-1 |
| Online-Zugang: | Resolving-System, Volltext: https://doi.org/10.1016/S1470-2045(19)30098-1 Verlag: http://www.sciencedirect.com/science/article/pii/S1470204519300981 |
| Verfasserangaben: | Philipp Kickingereder, Fabian Isensee, Irada Tursunova, Jens Petersen, Ulf Neuberger, David Bonekamp, Gianluca Brugnara, Marianne Schell, Tobias Kessler, Martha Foltyn, Inga Harting, Felix Sahm, Marcel Prager, Martha Nowosielski, Antje Wick, Marco Nolden, Alexander Radbruch, Jürgen Debus, Heinz-Peter Schlemmer, Sabine Heiland, Michael Platten, Andreas von Deimling, Martin J van den Bent, Thierry Gorlia, Wolfgang Wick, Martin Bendszus, Klaus H Maier-Hein |
| Zusammenfassung: | We aimed to develop a framework relying on artificial neural networks (ANNs) for fully automated quantitative analysis of MRI in neuro-oncology to overcome the inherent limitations of manual assessment of tumour burden. |
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| Beschreibung: | Gesehen am 16.10.2019 |
| Beschreibung: | Online Resource |
| ISSN: | 1474-5488 |
| DOI: | 10.1016/S1470-2045(19)30098-1 |