2021
DOI: 10.1016/j.compbiomed.2020.104204
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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.

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Cited by 8 publications
(1 citation statement)
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“…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%