Advancing medical imaging research through standardization: The path to rapid development, rigorous validation, and robust reproducibility
K Jeon, WY Park, CE Kahn Jr, P Nagy… - Investigative …, 2023 - journals.lww.com
Artificial intelligence (AI) has made significant advances in radiology. Nonetheless,
challenges in AI development, validation, and reproducibility persist, primarily due to the …
challenges in AI development, validation, and reproducibility persist, primarily due to the …
Reproducible Radiomics Features from Multi‐MRI‐Scanner Test–Retest‐Study: Influence on Performance and Generalizability of Models
M Wennmann, LT Rotkopf, F Bauer… - Journal of Magnetic …, 2024 - Wiley Online Library
Background Radiomics models trained on data from one center typically show a decline of
performance when applied to data from external centers, hindering their introduction into …
performance when applied to data from external centers, hindering their introduction into …
3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients with Multiple Myeloma using Whole-body MRI
K Morita, S Karashima, T Terao, K Yoshida… - Journal of Medical …, 2024 - Springer
Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM)
are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques …
are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques …
Sexual Dimorphism of Radiomic Features in the Brain: An Exploratory Study Using 700 μm MP2RAGE MRI at 7 T
ME Mayerhoefer, TM Shepherd, M Weber… - Investigative …, 2023 - journals.lww.com
Objectives The aim of this study was to determine whether MRI radiomic features of key
cerebral structures differ between women and men, and whether detection of such …
cerebral structures differ between women and men, and whether detection of such …
[HTML][HTML] Comprehensive diagnostic model for osteosarcoma classification using CT imaging features
Y Wang, Z Wang, B Zhang, F Yang - Journal of Bone Oncology, 2024 - Elsevier
Objective The main objective of this study was to create and assess a detailed diagnostic
model with an optimizing feature selection algorithm that combines computed tomography …
model with an optimizing feature selection algorithm that combines computed tomography …
(Smoldering) multiple myeloma: mismatch between tumor load estimated from bone marrow biopsy at iliac crest and tumor load shown by MRI
F Bauer, S Sauer, N Weinhold, S Delorme… - Skeletal Radiology, 2023 - Springer
In multiple myeloma and its precursor stages, precise quantification of tumor load is of high
importance for diagnosis, risk assessment, and therapy response evaluation. Both whole …
importance for diagnosis, risk assessment, and therapy response evaluation. Both whole …
KI–MRT sagt Knochenmarkbefund voraus
S Krome - RöFo-Fortschritte auf dem Gebiet der …, 2024 - thieme-connect.com
Vorteile der MRT gegenüber der Knochenmarkbiopsie seien auch die Nichtinvasivität und
häufigere Wiederholbarkeit. Wennmann et al. überprüften mit 672 MRT von insgesamt 512 …
häufigere Wiederholbarkeit. Wennmann et al. überprüften mit 672 MRT von insgesamt 512 …
[引用][C] Editorial for “Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study: Influence on Performance and Generalizability of Models”
M Sabati, A Chauhan - Journal of Magnetic Resonance Imaging, 2024 - pure.kfas.org.kw
Editorial for “Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study:
Influence on Performance and Generalizability of Models” — مؤسسة الكويت للتقدم العلمي تخطي …
Influence on Performance and Generalizability of Models” — مؤسسة الكويت للتقدم العلمي تخطي …