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Open Access Green as soon as Postprint is submitted to ZB.
Image-based artefact removal in laser scanning microscopy.
IEEE Trans. Bio. Med. Eng. 67, 79-87 (2020)
Recent developments in laser scanning microscopy have greatly extended its applicability in cancer imaging beyond the visualization of complex biology, and opened up the possibility of quantitative analysis of inherently dynamic biological processes. However, the physics of image acquisition intrinsically means that image quality is subject to a tradeoff between a number of imaging parameters, including resolution, signal-to-noise ratio, and acquisition speed. We address the problem of geometric distortion, in particular, jaggedness artefacts that are caused by the variable motion of the microscope laser, by using a combination of image processing techniques. Image restoration methods have already shown great potential for post-acquisition image analysis. The performance of our proposed image restoration technique was first quantitatively evaluated using phantom data with different textures, and then qualitatively assessed using in vivo biological imaging data. In both cases, the presented method, comprising a combination of image registration and filtering, is demonstrated to have substantial improvement over state-of-the-art microscopy acquisition methods.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Image Processing ; Image Restoration ; Laser Scanning Microscopy
Language
english
Publication Year
2020
HGF-reported in Year
2020
ISSN (print) / ISBN
0018-9294
e-ISSN
0096-0616
Quellenangaben
Volume: 67,
Issue: 1,
Pages: 79-87
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publishing Place
New York, NY
Reviewing status
Peer reviewed
Institute(s)
Institute for Machine Learning in Biomed Imaging (IML)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-507100-001
Scopus ID
85077174126
PubMed ID
31034401
Erfassungsdatum
2022-09-07