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Found 2 papers, 1 papers with code
Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation
In this work, we propose an adaptive multi-scale online likelihood network (MONet) that adaptively learns in a data-efficient online setting from both an initial automatic segmentation and user interactions providing corrections.
VertXNet: An Ensemble Method for Vertebrae Segmentation and Identification of Spinal X-Ray
Our experimental results have shown that the proposed pipeline outperformed two SOTA segmentation models on our test dataset (MEASURE 1) with a mean Dice of 0. 90, vs. a mean Dice of 0. 73 for Mask R-CNN and 0. 72 for U-Net.
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