AutoPETIII: The Tracer Frontier What Frontier?
<|reference_start|>AutoPETIII: The Tracer Frontier What Frontier?: For the last three years, the AutoPET competition gathered the medical imaging community around a hot topic: lesion segmentation on Positron Emitting Tomography (PET) scans. Each year a different aspect of the problem is presented; in 2024 the multiplicity of existing and used tracers was at the core of the challenge. Specifically, this year's edition aims to develop a fully automatic algorithm capable of performing lesion segmentation on a PET/CT scan, without knowing the tracer, which can either be a FDG or PSMA-based tracer. In this paper we describe how we used the nnUNetv2 framework to train two sets of 6 fold ensembles of models to perform fully automatic PET/CT lesion segmentation as well as a MIP-CNN to choose which set of models to use for segmentation.<|reference_end|>
@article{mesbah2024autopetiii:,
    title={AutoPETIII: The Tracer Frontier. What Frontier?},
    author={Zacharia Mesbah, L'eo Mottay, Romain Modzelewski, Pierre Decazes,
  S'ebastien Hapdey, Su Ruan, S'ebastien Thureau},
    journal={arXiv preprint arXiv:2410.02807},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.02807},
    primaryClass={eess.IV cs.AI cs.CV}
}