
The author presents a novel approach, SimICL, combining visual in-context learning and masked image modeling to enhance ultrasound segmentation. By leveraging self-supervised learning techniques, the method achieves remarkable accuracy and efficiency in segmenting bony structures.


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improving-ultrasound-segmentation-with-visual-in-context-learning-and-masked-image-modeling


Improving Ultrasound Segmentation with Visual In-context Learning and Masked Image Modeling
