2 research outputs found
US-net for robust and efficient nuclei instance segmentation
We present a novel neural network architecture, US-Net, for robust nuclei
instance segmentation in histopathology images. The proposed framework
integrates the nuclei detection and segmentation networks by sharing their
outputs through the same foundation network, and thus enhancing the performance
of both. The detection network takes into account the high-level semantic cues
with contextual information, while the segmentation network focuses more on the
low-level details like the edges. Extensive experiments reveal that our
proposed framework can strengthen the performance of both branch networks in an
integrated architecture and outperforms most of the state-of-the-art nuclei
detection and segmentation networks.Comment: To appear in ISBI 201