Volumetric memory network for interactive medical image segmentation

Zhou, Tianfei; Li, Liulei; Bredell, Gustav; Li, Jianwu; Unkelbach, Jan; Konukoglu, Ender

doi:10.1016/j.media.2022.102599

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Zhou, T., Li, L., Bredell, G., Li, J., Unkelbach, J., & Konukoglu, E. (2023). Volumetric memory network for interactive medical image segmentation. Medical Image Analysis, 83, 102599. https://doi.org/10.1016/j.media.2022.102599

Abstract

Despite recent progress of automatic medical image segmentation techniques, fully automatic results usually fail to meet clinically acceptable accuracy, thus typically require further refinement. To this end, we propose a novel Volumetric Memory Network, dubbed as VMN, to enable segmentation of 3D medical images in an interactive manner. Provided by user hints on an arbitrary slice, a 2D interaction network is firstly employed to produce an initial 2D segmentation for the chosen slice. Then, the VMN propagates the initial segmentation