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Quantitative Assessment of Tumor Contact with Neurogenic Zones and Its Effects on Survival: Insights beyond Traditional Predictors

Cancers, 2024-05, Vol.16 (9), p.1743

2024

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Predicting Glioblastoma Recurrence from Preoperative MR Scans Using Fractional-Anisotropy Maps with Free-Water Suppression

Cancers, 2020-03, Vol.12 (3), p.728

2020

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Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas

Cancers, 2023-04, Vol.15 (8), p.2355

2023

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Sequential and Hybrid PET/MRI Acquisition in Follow-Up Examination of Glioblastoma Show Similar Diagnostic Performance

Cancers, 2022-12, Vol.15 (1), p.83

2022

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Molecular imaging of gliomas

Clinical neuropathology, 2023-07, Vol.42 (4), p.131-139

2023

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Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT

Radiology, 2024-03, Vol.310 (3), p.e231429

2024

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Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model

Neuro-oncology advances, 2024-01, Vol.6 (1), p.vdad171-vdad171

2024

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NIMG-27. GLIOBLASTOMA IN THE MAKING? ADVANCED IMAGING TELLS "MOLECULAR GLIOBLASTOMA" APART FROM ASTROCYTOMA

Neuro-oncology (Charlottesville, Va.), 2023-11, Vol.25 (Supplement_5), p.v191-v191

2023

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NIMG-17. TOWARDS IMAGE - BASED PERSONALIZATION OF GLIOBLASTOMA THERAPY: A COMPREHENSIVE VALIDATION STUDY OF A NOVEL, DEEP LEARNING - DRIVEN TUMOR GROWTH MODEL FOR INDIVIDUALIZED RADIOTHERAPY

Neuro-oncology (Charlottesville, Va.), 2023-11, Vol.25 (Supplement_5), p.v188-v188

2023

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Resolving spatial response heterogeneity in glioblastoma

European journal of nuclear medicine and molecular imaging, 2024-10, Vol.51 (12), p.3685-3695

2024

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Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives

Strahlentherapie und Onkologie, 2024-08

2024

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Exploring molecular glioblastoma: Insights from advanced imaging for a nuanced understanding of the molecularly defined malignant biology

Neuro-oncology advances, 2024-01, Vol.6 (1), p.vdae106

2024

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KORREKTUR DER WASSERKONTAMINATION IN DER DTI: VERBESSERTE VORHERSAGE DER REZIDIVLOKALISATION IN GLIOBLASTOMEN BEREITS IM PRAOPERATIVEN MRT

Clinical neuroradiology (Munich), 2019-09, Vol.29 (S1), p.S15

2019

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Trainee Research Prizes from the 2019 RSNA Scientific Assembly and Annual Meeting

Radiology, 2020-07, Vol.296 (1), p.1-3

2020

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Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma

Neuro-oncology advances, 2024-01, Vol.6 (1), p.vdae080

2024

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Quantitative Assessment of Tumor Contact with Neurogenic Zones and Its Effects on Survival: Insights beyond Traditional Predictors

Predicting Glioblastoma Recurrence from Preoperative MR Scans Using Fractional-Anisotropy Maps with Free-Water Suppression

Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas

Sequential and Hybrid PET/MRI Acquisition in Follow-Up Examination of Glioblastoma Show Similar Diagnostic Performance

Molecular imaging of gliomas

Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT

Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model

NIMG-27. GLIOBLASTOMA IN THE MAKING? ADVANCED IMAGING TELLS "MOLECULAR GLIOBLASTOMA" APART FROM ASTROCYTOMA

NIMG-17. TOWARDS IMAGE - BASED PERSONALIZATION OF GLIOBLASTOMA THERAPY: A COMPREHENSIVE VALIDATION STUDY OF A NOVEL, DEEP LEARNING - DRIVEN TUMOR GROWTH MODEL FOR INDIVIDUALIZED RADIOTHERAPY

Resolving spatial response heterogeneity in glioblastoma

Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives

Exploring molecular glioblastoma: Insights from advanced imaging for a nuanced understanding of the molecularly defined malignant biology

KORREKTUR DER WASSERKONTAMINATION IN DER DTI: VERBESSERTE VORHERSAGE DER REZIDIVLOKALISATION IN GLIOBLASTOMEN BEREITS IM PRAOPERATIVEN MRT

Trainee Research Prizes from the 2019 RSNA Scientific Assembly and Annual Meeting

Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma

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