Pretrained models for 3D segmentation of neuroendocrine tumors in PET/CT with nnU-Net

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UID: 11202

Author(s): Santilli, Alice*, Panyam, Prashanth*, Autz, Arthur*, Wray, Rick*, Philip, John*, Elnajjar, Pierre*, Swinburne, Nathaniel*, Mayerhoefer, Marius E* * MSK affiliated

Description: Description from Zenodo:

"In this repository we share models trained on a large annotated dataset of PET DOTATATE images using the nnU-Net V1 pipeline. This version of the pipeline can be found here. Given the modularity of the nnU-net framework, we make these models public with the hopes of allowing other institutions to benefit from our pre-training and to improve upon and verify the generalizability of the models. More information about these models can be found in this repository : https://github.com/AliceSantilli/nnUNet

Or in our paper titled "Automated full body tumor segmentation in DOTATATE PET/CT for neuroendocrine cancer patients" published in IJCARS, DOI:10.1007/s11548-023-02968-1

These models were trained at Memorial Sloan Kettering Cancer Center. The dataset was comprised of 915 scan volumes, each with a PET-DOTATATE scan and attenuation-correction CT pair. Unfortunately, at this time we will not be making the data public.

For more information, contact Alice Santilli at santila@mskcc.org"

Subject(s)

Image Processing, Computer-Assisted

Neuroendocrine Tumors

Positron Emission Tomography Computed Tomography

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