Latent-to-Latent Flow for Volumetric Stochastic Segmentation
This work introduces a latent-to-latent flow technique for stochastic segmentation of medical volumes via encoded representations of both the image and label space, improving efficiency up to 14x compared with full resolution models while maintaining clinically relevant performance.
Omar Todd, Sooha Kim, Raghav Mehta et al.
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