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Online Ressourcen 1 Fractional amplitude of low-frequency fluctuations associated with μ-opioid and dopamine receptor distributions in the central nervous system after high-intensity exercise bouts
Boecker, Henning. - Bonn : Universitäts- und Landesbibliothek Bonn, 2024
Online Ressource
Artikel 2 Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance
Enthalten in European radiology 23.10.2024: 1-11
Online Ressource
Online Ressourcen 3 Entwicklung einer Radiomics-Signatur sowie eines Deep Learning Algorithmus für die Prädiktion von signifikanten Prostatakarzinomen
Schenk, Sarah Elena. - Heidelberg : Universitätsbibliothek Heidelberg, 2023
Online Ressource
Online Ressourcen 4 How Controlled is the Expansion of VIATORR CX?
Dell, Tatjana. - Aachen : Universitätsbibliothek der RWTH Aachen, 2023
Online Ressource
Bücher 5 Quantitative diffusion-weighted magnetic resonance imaging in prostate and rectal cancer
Wichtmann, Barbara. - Heidelberg, 2023
Vorhanden in Leipzig Vorhanden in Frankfurt
Artikel 6 Development of image-based decision support systems utilizing information extracted from radiological free-text report databases with text-based transformers
Enthalten in European radiology 7.11.2023: 1-10
Online Ressource
Artikel 7 Deep learning–based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment
Enthalten in European radiology 12.8.2023: 1-8
Online Ressource
Artikel 8 Total marrow irradiation versus total body irradiation using intensity-modulated helical tomotherapy
Enthalten in Journal of cancer research and clinical oncology 6.1.2023: 1-9
Online Ressource
Online Ressourcen 9 Are we there yet? The value of deep learning in a multicenter setting for response prediction of locally advanced rectal cancer to neoadjuvant chemoradiotherapy
Wichtmann, Barbara. - Frankfurt am Main : Universitätsbibliothek Johann Christian Senckenberg, 2022
Online Ressource
Artikel 10 Deep learning for standardized, MRI-based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema
Enthalten in European radiology 17.8.2022: 1-9
Online Ressource


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