13 citations · 26 across the 3 of their papers we have counts for
4 papers
GLOW-FDG: Generalized cancer LesiOn Whole-body segmentation model for F-FDG-PET/CT
Maksym Fritsak, Maximilian Rokuss, Hubert S. Gabryś +10
Whole-body fluorodeoxyglucose positron emission tomography combined with computed tomography is widely used in cancer care, but manual lesion delineation is slow, subjective, and d…
The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information
D. Abler, O. Pusterla, A. Joye-Kühnis +19
Background: Radiomics shows promise in characterizing glioblastoma, but its added value over clinical and molecular predictors has yet to be proven. This study assessed the added v…
Exploring the Capabilities and Limitations of Large Language Models for Radiation Oncology Decision Support
Florian Putz, Marlen Haderleina, Sebastian Lettmaier +3
Thanks to the rapidly evolving integration of LLMs into decision-support tools, a significant transformation is happening across large-scale systems. Like other medical fields, the…
Multicenter Privacy-Preserving Model Training for Deep Learning Brain Metastases Autosegmentation
Yixing Huang, Zahra Khodabakhshi, Ahmed Gomaa +7
Objectives: This work aims to explore the impact of multicenter data heterogeneity on deep learning brain metastases (BM) autosegmentation performance, and assess the efficacy of a…