Lite Swin UNETR: A Lightweight Version of Swin UNETR for Efficient 3D Medical Image Segmentation

Junyoung Park; Minyoung Park; Taikyeong Jeong; Sungwook Yu

doi:10.1007/s42835-025-02392-2

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Lite Swin UNETR: A Lightweight Version of Swin UNETR for Efficient 3D Medical Image Segmentation

Junyoung Park Minyoung Park Taikyeong Jeong Sungwook Yu

Year: 2025 Journal: Journal of Electrical Engineering and Technology Vol: 20 (8)Pages: 5455-5469 Publisher: Springer Science+Business Media

DOI: 10.1007/s42835-025-02392-2

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Keywords:

Artificial intelligence Computer vision Computer science Image segmentation Segmentation Image (mathematics) Computer graphics (images)

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Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Lite Swin UNETR: A Lightweight Version of Swin UNETR for Efficient 3D Medical Image Segmentation

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