Journal
2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019)
Volume -, Issue -, Pages 44-47Publisher
IEEE
DOI: 10.1109/isbi.2019.8759530
Keywords
US-Net; nuclei detection; nuclei segmentation; histopathology image analysis
Funding
- EPSRC [EP/N034708/1]
- EPSRC [EP/N034708/1] Funding Source: UKRI
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available