13 citations · 37 across the 4 of their papers we have counts for
6 papers
ProSona: Prompt-Guided Personalization for Multi-Expert Medical Image Segmentation
Aya Elgebaly, Nikolaos Delopoulos, Juliane Hörner-Rieber +11
Automated medical image segmentation suffers from high inter-observer variability, particularly in tasks such as lung nodule delineation, where experts often disagree. Existing app…
Simultaneous optimization of non-coplanar beam orientations and cumulative EQD2 distribution for high-dose reirradiation of locoregionally recurrent non-small cell lung cancer
Nathan Torelli, Jonas Willmann, Katja Daehler +3
Background and Purpose: Reirradiation for non-small cell lung cancer (NSCLC) is commonly delivered using coplanar techniques. In this study, we developed a beam orientation optimiz…
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…
Automatized Self-Supervised Learning for Skin Lesion Screening
Vullnet Useini, Stephanie Tanadini-Lang, Quentin Lohmeyer +4
Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial f…