TY  - EJOUR
AU  - Ma, Jun
AU  - Xie, Ronald
AU  - Ayyadhury, Shamini
AU  - Ge, Cheng
AU  - Gupta, Anubha
AU  - Gupta, Ritu
AU  - Gu, Song
AU  - Zhang, Yao
AU  - Lee, Gihun
AU  - Kim, Joonkee
AU  - Lou, Wei
AU  - Li, Haofeng
AU  - Upschulte, Eric
AU  - Dickscheid, Timo
AU  - de Almeida, José Guilherme
AU  - Wang, Yixin
AU  - Han, Lin
AU  - Yang, Xin
AU  - Labagnara, Marco
AU  - Rahi, Sahand Jamal
AU  - Kempster, Carly
AU  - Pollitt, Alice
AU  - Espinosa, Leon
AU  - Mignot, Tâm
AU  - Middeke, Jan Moritz
AU  - Eckardt, Jan-Niklas
AU  - Li, Wangkai
AU  - Li, Zhaoyang
AU  - Cai, Xiaochen
AU  - Bai, Bizhe
AU  - Greenwald, Noah F.
AU  - Van Valen, David
AU  - Weisbart, Erin
AU  - Cimini, Beth A.
AU  - Li, Zhuoshi
AU  - Zuo, Chao
AU  - Brück, Oscar
AU  - Bader, Gary D.
AU  - Wang, Bo
TI  - The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
JO  - arxiv
PB  - arXiv
M1  - FZJ-2023-03643
PY  - 2023
AB  - Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyperparameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods, but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.
KW  - Image and Video Processing (eess.IV) (Other)
KW  - Computer Vision and Pattern Recognition (cs.CV) (Other)
KW  - Machine Learning (cs.LG) (Other)
KW  - Quantitative Methods (q-bio.QM) (Other)
KW  - FOS: Electrical engineering, electronic engineering, information engineering (Other)
KW  - FOS: Computer and information sciences (Other)
KW  - FOS: Biological sciences (Other)
LB  - PUB:(DE-HGF)25
DO  - DOI:10.48550/arXiv.2308.05864
UR  - https://juser.fz-juelich.de/record/1015298
ER  -