2021
DOI: 10.1016/j.compbiomed.2020.104204
|View full text |Cite
|
Sign up to set email alerts
|

A crowdsourcing semi-automatic image segmentation platform for cell biology

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 41 publications
(68 reference statements)
0
1
0
Order By: Relevance
“…The medical domain is where the majority of the research and development of annotation tools based on ontologies takes place. The annotation method with a crowdsourcing approach to medical data produces a knowledge base for mental health literature, segmentation of cellular biology images, and the retrieval process of electronic medical records [13]- [15]. Annotation tools have also been developed for labeling multimedia data [16], [17] with the help of a previously trained semantic ontology.…”
Section: Introductionmentioning
confidence: 99%
“…The medical domain is where the majority of the research and development of annotation tools based on ontologies takes place. The annotation method with a crowdsourcing approach to medical data produces a knowledge base for mental health literature, segmentation of cellular biology images, and the retrieval process of electronic medical records [13]- [15]. Annotation tools have also been developed for labeling multimedia data [16], [17] with the help of a previously trained semantic ontology.…”
Section: Introductionmentioning
confidence: 99%