SC-Track: A Biologically Inspired Algorithm for Generating Accurate Single Cell Lineages from Noisy Deep Learning based Cell Segmentations

Name: SC-Track: A Biologically Inspired Algorithm for Generating Accurate Single Cell Lineages from Noisy Deep Learning based Cell Segmentations
Keywords: cell division, convolutional neural networks, timelapse microscopy imaging, deep learning, cell cycle, single cell tracking

Li Chengxin; Xie Shuangshuang; Wang Jiaqi; Septavera Sharvia; Chan Kuan Yoow

Found an issue? Give us feedback

ZENODOarrow_drop_down

ZENODO

Article . 2023

Data sources: ZENODO

ZENODO

Article . 2023

Data sources: Datacite

SC-Track: A Biologically Inspired Algorithm for Generating Accurate Single Cell Lineages from Noisy Deep Learning based Cell Segmentations

descriptionPublicationkeyboard_double_arrow_right Article 25 Aug 2023Publisher:Zenodo

Authors: Li Chengxin; Xie Shuangshuang; Wang Jiaqi; Septavera Sharvia; Chan Kuan Yoow;

doi: 10.5281/zenodo.8284987

SC-Track: A Biologically Inspired Algorithm for Generating Accurate Single Cell Lineages from Noisy Deep Learning based Cell Segmentations

- Summary
- Subjects
- Metrics

Abstract

SC-Track is an efficient algorithm for dynamic tracking of single cells on different time-lapse microscope images. see more detail at https://github.com/chan-labsite/SC-Track

Related Organizations

University of Hull
United Kingdom
Zhejiang Ocean University
China (People's Republic of)

Keywords

cell division, convolutional neural networks, timelapse microscopy imaging, deep learning, cell cycle, single cell tracking

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average