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A crowdsourcing semi-automatic image segmentation platform for cell biology

Bafti, Saber Mirzaee, Ang, Chee Siang, Hossain, Md. Moinul, Marcelli, Gianluca, Alemany-Fornes, Marc, Tsaousis, Anastasios D. (2021) A crowdsourcing semi-automatic image segmentation platform for cell biology. A crowdsourcing semi-automatic image segmentation platform for cell biology, . Article Number 104204. ISSN 0010-4825. (doi:10.1016/j.compbiomed.2020.104204) (KAR id:85323)

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State-of-the-art computer-vision algorithms rely on big and accurately annotated data, which are expensive, laborious and time-consuming to generate. This task is even more challenging when it comes to microbiological images, because they require specialized expertise for accurate annotation. Previous studies show that crowdsourcing and assistive-annotation tools are two potential solutions to address this challenge. In this work, we have developed a web-based platform to enable crowdsourcing annotation of image data; the platform is powered by a semi-automated assistive tool to support non-expert annotators to improve the annotation efficiency. The behavior of annotators with and without the assistive tool is analyzed, using biological images of different complexity. More specifically, non-experts have been asked to use the platform to annotate microbiological images of gut parasites, which are compared with annotations by experts. A quantitative evaluation is carried out on the results, confirming that the assistive tools can noticeably decrease the non-expert annotation�s cost (time, click, interaction, etc.) while preserving or even improving the annotation�s quality. The annotation quality of non-experts has been investigated using IOU (intersection of union), precision and recall; based on this analysis we propose some ideas on how to better design similar crowdsourcing and assistive platforms.

Item Type: Article
DOI/Identification number: 10.1016/j.compbiomed.2020.104204
Additional information: Unmapped bibliographic data: DA - 2021/01/02/ [EPrints field already has value set] JO - Computers in Biology and Medicine [Field not mapped to EPrints]
Uncontrolled keywords: Semi-auto segmentation, Object detection, Computational biology, Crowdsourcing, Image annotation, Instance segmentation
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Moinul Hossain
Date Deposited: 05 Jan 2021 11:56 UTC
Last Modified: 21 Nov 2021 23:10 UTC
Resource URI: (The current URI for this page, for reference purposes)
Ang, Chee Siang:
Hossain, Md. Moinul:
Marcelli, Gianluca:
Tsaousis, Anastasios D.:
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