https://github.com/why19991/InSeg

https://github.com/why19991/InSeg

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/why19991/InSeg
• Owner: why19991
• License: mit
• Created: 2024-03-27T07:55:16.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-03-28T13:22:59.000Z (about 1 year ago)
• Last Synced: 2024-10-29T17:49:14.807Z (8 months ago)
• Language: Python
• Size: 338 KB
• Stars: 10
• Watchers: 1
• Forks: 0
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-segmentation-and-graph-method - code

README

        
# InSeg  

### Incremental Nuclei Segmentation from Histopathological Images  

### via Future-class Awareness and Compatibility-inspired Distillation [CVPR 2024]  

###### Huyong Wang1, Huisi Wu1, Jing Qin2  

###### 1College of Computer Science and Software Engineering, Shenzhen University  

###### 2Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University  

# Method  



  

  


# Notes  

Due to the confidentiality agreement in commercial cooperation, we only provide codes of core modules and the whole trainable models for the convenience of comparisons.  

# Environment  

* Python>=3.8  

* Pytorch>=1.8.1

* Install [inplace_abn](https://github.com/mapillary/inplace_abn)

# Thanks  

This code is heavily borrowed from [[EWF](https://github.com/schuy1er/EWF_official)] and [[PLOP](https://github.com/arthurdouillard/CVPR2021_PLOP)]. We appreciate their contributions to this community.