Author

M. Ingrisch

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Open access Sep 2026

Fully Automated Segmentation of [18F]FDG and [68Ga]/[18F]PSMA PET/CT Images via Data-Centric Deep Learning.

The purpose of this study was to develop and validate lesion identification in oncologic nuclear imaging (LION), an open-source PET-only tumor segmentation pipeline for [18F]FDG and prostate-specific membrane antigen (PSMA)-targeted PET/CT, and to investigate how training data characteristics influence segmentation per...

M. Pires, S. Gutschmayer, E. Bergalla et al. · Journal of Nuclear Medicine · 1 citation

Open access Jul 2026

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systems

Chronicle is introduced, an explainable transformer that learns from entire patient trajectories, predicts diverse clinical outcomes throughout the disease course while capturing both short- and long-term temporal dependencies, providing a scalable framework to support individualized treatment decisions.

P. Keyl, N. Kiermeyer, J. Bosserhoff et al. · medRxiv · 0 citations