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Detection of tubule boundaries based on circular shortest path and polar-transformation of arbitrary shapes
Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-4255-5130
2016 (English)In: Journal of Microscopy, ISSN 1365-2818Article in journal (Refereed) Epub ahead of print
Abstract [en]

In studies of germ cell transplantation, counting cells and measuring tubule diameters from different populations using labelled antibodies are important measurement processes. However, it is slow and sanity grinding to do these tasks manually. This paper proposes a way to accelerate these processes using a new image analysis framework based on several novel algorithms: centre points detection of tubules, tubule shape classification, skeleton-based polar-transformation, boundary weighting of polar-transformed image, and circular shortest path smoothing. The framework has been tested on a dataset consisting of 27 images which contain a total of 989 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually and the novel approach can achieve a better performance than two existing methods.

Place, publisher, year, edition, pages
Wiley , 2016.
Keyword [en]
Boundary detection; boundary weighting; circular shortest path; polar-transform; testis images; tubule boundary
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-129032DOI: 10.1111/jmi.12421PubMedID: 27172164OAI: oai:DiVA.org:liu-129032DiVA: diva2:934622
Available from: 2016-06-09 Created: 2016-06-09 Last updated: 2016-06-27

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Pham, Tuan
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Department of Biomedical EngineeringFaculty of Science & Engineering
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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