General Vision Encoder Features as Guidance in Medical Image Registration

doi:doi:10.57702/g5wv2w7q

General Vision Encoder Features as Guidance in Medical Image Registration

General vision encoders like DINOv2 and SAM have recently transformed computer vision. Even though they are trained on natural images, encoder models have excelled in medical imaging, e.g., in classification, segmentation, and registration.

BibTex:

@dataset{Fryderyk_Kögl_and_Anna_Reithmeir_and_Vasiliki_Sideri-Lampretsa_and_Ines_Machado_and_Rickmer_Braren_and_Daniel_Rückert_and_Julia_A_Schnabel_and_Veronika_A_Zimmer_2024,
    abstract = {General vision encoders like DINOv2 and SAM have recently transformed computer vision. Even though they are trained on natural images, encoder models have excelled in medical imaging, e.g., in classification, segmentation, and registration.},
    author = {Fryderyk Kögl and Anna Reithmeir and Vasiliki Sideri-Lampretsa and Ines Machado and Rickmer Braren and Daniel Rückert and Julia A. Schnabel and Veronika A. Zimmer},
    doi = {10.57702/g5wv2w7q},
    institution = {No Organization},
    keyword = {'DINOv2', 'SAM', 'general vision encoders', 'medical image registration'},
    month = {dec},
    publisher = {TIB},
    title = {General Vision Encoder Features as Guidance in Medical Image Registration},
    url = {https://service.tib.eu/ldmservice/dataset/general-vision-encoder-features-as-guidance-in-medical-image-registration},
    year = {2024}
}