Automated segmentation of lesions and organs at risk on [<sup>68</sup>Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR.

Journal Information

Full Title: Cancer Imaging

Abbreviation: Cancer Imaging

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Diagnostic Imaging

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
4/6
66.7% Transparent
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Evidence found in paper:

"our code is available at: https://github com/elmirayazdani/lesions-oars-segmentation-psma-petct-ssl-swinunetr .; the code to reproduce the experiments is available at the following url: https://github com/elmirayazdani/lesions-oars-segmentation-psma-petct-ssl-swinunetr ."

Evidence found in paper:

"Declaration Ethics approval and consent to participateWe retrospectively collected the patient data for this research. The Ethics Committee of IUMS waived this in the ethics approval IR.IUMS.FMD.REC.1401.505. Consent for publicationInformed consent was waived by the ethics committee (IR.IUMS.FMD.REC.1401.505). Competing interestsThe author declares that there are no conflicts of interest. Competing interests The author declares that there are no conflicts of interest."

Evidence found in paper:

"Funding This work is based upon research funded by Iran National Science Foundation (INSF) under project No. 4020727."

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Open Access
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Last Updated: Aug 05, 2025