U-Net: Convolutional Network for Segmentation

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Presentation transcript:

U-Net: Convolutional Network for Segmentation Presented by: Chanon Chantaduly

What does a U-Net do? Learns Segmentation Output Segmentation Map Input Image

U-Net Architecture Ronneberger et al. (2015) U-net Architecture

U-Net Architecture “Contraction” Phase - Increases field of view - Lose Spatial Information Ronneberger et al. (2015) U-net Architecture

Create High Resolution U-Net Architecture “Expansion” Phase Create High Resolution Mapping Ronneberger et al. (2015) U-net Architecture

U-Net Architecture Concatenate with high-resolution feature maps from the Contraction Phase Ronneberger et al. (2015) U-net Architecture

U-Net Summary Contraction Phase Expansion Phase Reduce spatial dimension, but increases the “what.” Expansion Phase Recovers object details and the dimensions, which is the “where.” Concatenating feature maps from the Contraction phase helps the Expansion phase with recovering the “where” information.

Author Results Ronneberger et al. (2015) ISBI cell tracking challenge