TopoSeg: Topology-Aware Nuclear Instance Segmentation
Author:
Affiliation:
1. Peking University,School of Electronic and Computer Engineering,Shenzhen,China
2. Sun Yat-sen University,Guangzhou,China
3. Peng Cheng Laboratory,Shenzhen,China
4. Tsinghua University,Department of Automation and BNRist,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377779.pdf?arnumber=10377779
Reference28 articles.
1. A Persistent Homology-Based Topological Loss for CNN-Based Multiclass Segmentation of CMR
2. DCAN: Deep contour-aware networks for object instance segmentation from histology images
3. CPP-Net: Context-Aware Polygon Proposal Network for Nucleus Segmentation
4. A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
5. Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology
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1. Multi-Task Learning with Graph-Guided Feature Fusion Module for Nuclear Instance Segmentation;2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE);2024-03-01
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