Additional file 1 of Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR

Yazdani, Elmira; Karamzadeh-Ziarati, Najme; Cheshmi, Seyyed Saeid; Sadeghi, Mahdi; Geramifar, Parham; Vosoughi, Habibeh; Jahromi, Mahmood Kazemi; Kheradpisheh, Saeed Reza

doi:10.6084/m9.figshare.25322912.v1

40644_2024_675_MOESM1_ESM.docx (23.17 kB)

Additional file 1 of Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR

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posted on 2024-03-01, 05:20 authored by Elmira Yazdani, Najme Karamzadeh-Ziarati, Seyyed Saeid Cheshmi, Mahdi Sadeghi, Parham Geramifar, Habibeh Vosoughi, Mahmood Kazemi Jahromi, Saeed Reza Kheradpisheh

Supplementary Material 1: S1. Patient characteristics. S2. Pre-training loss function calculation. S3. Evaluation metrics

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Iran University of Medical Sciences

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Prostate cancer PSMA PET/CT Segmentation Lesion detection Neural network Deep-learning Swin UNETR Self-supervised learning

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Additional file 1 of Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR

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Iran University of Medical Sciences

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