Alexander Herold
5 Papers
Alexander Herold is an academic researcher. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 1, co-authored 4 publications.
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Papers
Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study.
Nina Bastati,Matthias Perkonigg,Daniel Sobotka,Sarah Poetter-Lang,Romana Fragner,Andrew Beer,Alina Messner,Martin L. Watzenboeck,Svitlana Pochepnia,Alexander Herold,Antonia Kristic,Jacqueline C. Hodge,S. Traussnig,Michael Trauner,Ahmed Ba-Ssalamah,Georg Langs +15 more
TL;DR: In this article , the authors compared unsupervised deep clustering (UDC) to fat fraction (FF) and relative liver enhancement (RLE) on Gd-EOB-DTPA-enhanced MRI to distinguish simple steatosis from non-alcoholic steatohepatitis (NASH), using histology as the gold standard.
The synergistic effect of PET/MRI in whole-body oncologic imaging: an Expert Review
Felipe S. Furtado,Mina Hesami,Shaunagh McDermott,H. Kulkarni,Alexander Herold,Onofrio A. Catalano +5 more
TL;DR: A narrative overview of the literature summarizes the findings of published research articles on PET/MRI for oncology indexed in the online databases Google Scholar, PubMed, and Scopus, from its commercial introduction in 2011 to the present.
Added value of quantitative, multiparametric 18F-FDG PET/MRI in the locoregional staging of rectal cancer
Alexander Herold,Christian Wassipaul,Michael Weber,Florian Lindenlaub,Sazan Rasul,Anton Stift,Judith Stift,Marius E. Mayerhoefer,Marcus Hacker,Ahmed Ba-Ssalamah,Alexander Haug,Dietmar Tamandl +11 more
TL;DR: Multiparametric PET-MRI can improve identification of locally advanced tumors and, hence, help in treatment stratification and provide additional information on RC tumor biology and may have prognostic value.
Improving vessel segmentation with multi-task learning and auxiliary data available only during model training
Daniel Sobotka,Alexander Herold,Matthias Perkonigg,Lucian Beer,Nina Bastati,Alina Sablatnig,Ahmed Ba-Ssalamah,Georg Langs +7 more
TL;DR: A multi-task learning framework improves liver vessel segmentation in MRI without contrast enhancement by leveraging auxiliary contrast-enhanced data available only during training, reducing the need for annotated examples and enhancing feature representation.
Influence of dilution on arterial-phase artifacts and signal intensity on gadoxetic acid–enhanced liver MRI
Sarah Poetter-Lang,Gregor Dovjak,Alina Messner,Raphael Ambros,Stephan H. Polanec,Pascal A. T. Baltzer,Antonia Kristic,Alexander Herold,Jacqueline C. Hodge,Michael Weber,Nina Bastati,Ahmed Ba-Ssalamah +11 more
TL;DR: In this article , the effect of gadoxetic acid-enhanced liver MRIs performed at 1 ml/s, first with non-diluted (ND), then with 1:1 (D) contrast.