Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model
Joint Authors
Crookes, Danny
Zhou, H.
Zhang, Kun
Zhang, Hongbin
Li, Ling
Shao, Yeqin
Liu, Dong
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-03
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Zebrafish embryo fluorescent vessel analysis, which aims to automatically investigate the pathogenesis of diseases, has attracted much attention in medical imaging.
Zebrafish vessel segmentation is a fairly challenging task, which requires distinguishing foreground and background vessels from the 3D projection images.
Recently, there has been a trend to introduce domain knowledge to deep learning algorithms for handling complex environment segmentation problems with accurate achievements.
In this paper, a novel dual deep learning framework called Dual ResUNet is developed to conduct zebrafish embryo fluorescent vessel segmentation.
To avoid the loss of spatial and identity information, the U-Net model is extended to a dual model with a new residual unit.
To achieve stable and robust segmentation performance, our proposed approach merges domain knowledge with a novel contour term and shape constraint.
We compare our method qualitatively and quantitatively with several standard segmentation models.
Our experimental results show that the proposed method achieves better results than the state-of-art segmentation methods.
By investigating the quality of the vessel segmentation, we come to the conclusion that our Dual ResUNet model can learn the characteristic features in those cases where fluorescent protein is deficient or blood vessels are overlapped and achieves robust performance in complicated environments.
American Psychological Association (APA)
Zhang, Kun& Zhang, Hongbin& Zhou, H.& Crookes, Danny& Li, Ling& Shao, Yeqin…[et al.]. 2019. Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1129599
Modern Language Association (MLA)
Zhang, Kun…[et al.]. Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1129599
American Medical Association (AMA)
Zhang, Kun& Zhang, Hongbin& Zhou, H.& Crookes, Danny& Li, Ling& Shao, Yeqin…[et al.]. Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1129599
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1129599