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In this work, we present our proposed method to segment the pulmonaryarteries from the CT scans using Swin UNETR and U-Net-based deep neural networkarchitecture. Six models, three models based on Swin UNETR, and three modelsbased on 3D U-net with residual units were ensemble using a weighted average tomake the final segmentation masks. Our team achieved a multi-level dice scoreof 84.36 percent through this method. The code of our work is available on thefollowing link: https://github.com/akansh12/parse2022. This work is part of theMICCAI PARSE 2022 challenge.

PARSE challenge 2022: Pulmonary Arteries Segmentation using Swin U-Net Transformer(Swin UNETR) and U-Net