title | booktitle | year | volume | series | month | publisher | url | abstract | layout | issn | id | tex_title | firstpage | lastpage | page | order | cycles | bibtex_editor | editor | bibtex_author | author | date | address | container-title | genre | issued | extras | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Semi-Supervised Cell Instance Segmentation for Multi-Modality Microscope Images |
Proceedings of the NeurIPS Challenge on Cell Segmentation in Muliti-modality Microscopy Images |
2022 |
212 |
Proceedings of Machine Learning Research |
0 |
PMLR |
Many clinical and biological tasks depend on accurate cell instance segmentation. Currently, the rapid development of deep learning realizes the automation of cell segmentation, which significantly decreases the workload of clinicians and researchers. However, most existing cell segmentation frameworks are fully supervised and modality-specific. Towards this end, this paper proposes a semi-supervised cell instance segmentation framework for multi-modality microscope images. Firstly, |
inproceedings |
2640-3498 |
wang23a |
Semi-Supervised Cell Instance Segmentation for Multi-Modality Microscope Images |
1 |
11 |
1-11 |
1 |
false |
Ma, Jun and Xie, Ronald and Gupta, Anubha and Guilherme de Almeida, Jos\'e and Bader, Gary D. and Wang, Bo |
|
Wang, Ziyue and Fang, Zijie and Chen, Yang and Yang, Zexi and Liu, Xinhao and Zhang, Yongbing |
|
2023-06-04 |
Proceedings of The Cell Segmentation Challenge in Multi-modality High-Resolution Microscopy Images |
inproceedings |
|