Marianne Schell
Overview
Explore the profile of Marianne Schell including associated specialties, affiliations and a list of published articles.
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Articles
17
Citations
534
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Recent Articles
1.
Foltyn-Dumitru M, Rastogi A, Cho J, Schell M, Mahmutoglu M, Kessler T, et al.
Neurooncol Adv
. 2025 Jan;
7(1):vdae230.
PMID: 39780768
Background: This study aimed to explore the potential of the Advanced Data Analytics (ADA) package of GPT-4 to autonomously develop machine learning models (MLMs) for predicting glioma molecular types using...
2.
Mahmutoglu M, Rastogi A, Schell M, Foltyn-Dumitru M, Baumgartner M, Maier-Hein K, et al.
Eur Radiol Exp
. 2024 Oct;
8(1):111.
PMID: 39382818
The growing use of artificial neural network (ANN) tools for computed tomography angiography (CTA) data analysis underscores the necessity for elevated data protection measures. We aimed to establish an automated...
3.
Foltyn-Dumitru M, Mahmutoglu M, Brugnara G, Kessler T, Sahm F, Wick W, et al.
Eur Radiol
. 2024 Sep;
35(3):1351-1360.
PMID: 39251442
Objectives: This study examines clustering based on shape radiomic features and tumor volume to identify IDH-wildtype glioma phenotypes and assess their impact on overall survival (OS). Materials And Methods: This...
4.
Foltyn-Dumitru M, Alzaid H, Rastogi A, Neuberger U, Sahm F, Kessler T, et al.
Neurooncol Adv
. 2024 Jul;
6(1):vdae112.
PMID: 39022646
Background: The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling...
5.
Foltyn-Dumitru M, Schell M, Sahm F, Kessler T, Wick W, Bendszus M, et al.
Neurooncol Adv
. 2024 Apr;
6(1):vdae043.
PMID: 38596719
Background: This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization...
6.
Rastogi A, Brugnara G, Foltyn-Dumitru M, Mahmutoglu M, Preetha C, Kobler E, et al.
Lancet Oncol
. 2024 Feb;
25(3):400-410.
PMID: 38423052
Background: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been...
7.
Foltyn-Dumitru M, Kessler T, Sahm F, Wick W, Heiland S, Bendszus M, et al.
Neuro Oncol
. 2023 Dec;
26(6):1099-1108.
PMID: 38153923
Background: While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional...
8.
Foltyn-Dumitru M, Schell M, Rastogi A, Sahm F, Kessler T, Wick W, et al.
Eur Radiol
. 2023 Sep;
34(4):2782-2790.
PMID: 37672053
Objectives: Radiomic features have demonstrated encouraging results for non-invasive detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data has led to poor generalizability. Here, we assessed the...
9.
Schell M, Foltyn-Dumitru M, Bendszus M, Vollmuth P
Sci Rep
. 2023 Jul;
13(1):11712.
PMID: 37474622
Deep learning segmentation algorithms can produce reproducible results in a matter of seconds. However, their application to more complex datasets is uncertain and may fail in the presence of severe...
10.
Schell M, Friederici A, Zaccarella E
Front Hum Neurosci
. 2022 Nov;
16:930849.
PMID: 36405085
Humans are equipped with the remarkable ability to comprehend an infinite number of utterances. Relations between grammatical categories restrict the way words combine into phrases and sentences. How the brain...