A self-supervised contrastive model using intra-sweep sampling and probe-location labels retrieves neck ultrasound views with 92.3% accuracy in simulation and shows qualitative feasibility on real patient data.
Nature reviews Clinical oncology 19(5), 306–327 (2022)
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Image Retrieval with Intra-Sweep Representation Learning for Neck Ultrasound Scanning Guidance
A self-supervised contrastive model using intra-sweep sampling and probe-location labels retrieves neck ultrasound views with 92.3% accuracy in simulation and shows qualitative feasibility on real patient data.