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Probe Rotation Estimation on Ten standard ultrasound planes

5.36MAE (Plane 1)EchoCLIP+ours
5.2765.8436.416.977Oct 8, 2025

Evaluation results

MethodLinks
EchoCLIP+oursTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=2.61M2025.105.365.935.985.625.36.595.838.198.4210.176.74
USFM+oursTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=3.97M2025.105.476.176.185.284.826.675.78.068.5610.186.71
BiomedCLIP+oursTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=3.94M2025.105.555.655.95.835.326.585.768.088.519.756.69
US-GuideNetTemporal context=Sequential, Pre-training dataset=ImageNet, Trained Params=22.05M, Backbone encoder=DeiT2025.105.887.217.2287.888.526.687.398.3911.137.83
Decision-TTemporal context=Sequential, Pre-training dataset=ImageNet, Trained Params=22.27M, Backbone encoder=DeiT2025.105.947.387.38.278.28.76.487.418.1810.897.88
EchoCLIPTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=88.41M2025.1066.697.26.876.757.516.658.999.0610.917.66
BiomedCLIPTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=86.15M2025.106.176.627.057.737.587.96.729.328.4310.467.8
USFMTemporal context=Sequential, Pre-training dataset=Ultrasound, Trained Params=87.04M2025.106.346.676.927.056.797.956.99.569.0710.827.81
EchoCLIPTemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=89.74M2025.106.867.528.518.448.479.187.039.318.8810.978.52
US-MAETemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=22.60M2025.107.117.618.238.558.569.057.269.679.4611.058.66
USFMTemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=92.94M2025.107.147.698.518.388.4197.189.389.3711.148.62
DINOv2Temporal context=Single-frame, Pre-training dataset=ImageNet, Trained Params=90.28M2025.107.217.828.758.668.429.047.279.419.3811.278.72
US-IJEPATemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=22.59M2025.107.247.757.988.738.469.067.579.729.4210.818.67
LVM-MedTemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=89.44M2025.107.267.948.628.818.859.277.599.659.6511.348.9
DeiTTemporal context=Single-frame, Pre-training dataset=ImageNet, Trained Params=22.60M2025.107.278.028.718.668.629.237.379.549.7111.288.84
BiomedCLIPTemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=89.50M2025.107.3388.848.888.859.387.8110.049.5911.629.03
US-MoCoTemporal context=Single-frame, Pre-training dataset=Ultrasound, Trained Params=22.60M2025.107.467.98.648.768.649.237.49.769.711.558.8