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Multiscale matters for part segmentation of instruments in robotic surgery
2020
IET Image Processing
A challenging aspect of instrument segmentation in robotic surgery is to distinguish different parts of the same instrument. Parts with similar textures are common in a practical instrument and are difficult to distinguish. In this work, the authors introduce an end-to-end recurrent model that comprises a multiscale semantic segmentation network and a refinement model. Specifically, the semantic segmentation network uniformly transforms the input images in multiple scales into a semantic mask,
doi:10.1049/iet-ipr.2020.0320
fatcat:oir6g37vvvawnbeelto2tamcla