Chapter title |
Image Degradation in Microscopic Images: Avoidance, Artifacts, and Solutions
|
---|---|
Chapter number | 2 |
Book title |
Focus on Bio-Image Informatics
|
Published in |
Advances in anatomy embryology and cell biology, May 2016
|
DOI | 10.1007/978-3-319-28549-8_2 |
Pubmed ID | |
Book ISBNs |
978-3-31-928547-4, 978-3-31-928549-8
|
Authors |
Roels, Joris, Aelterman, Jan, De Vylder, Jonas, Lippens, Saskia, Luong, Hiêp Q., Guérin, Christopher J., Philips, Wilfried, Joris Roels, Jan Aelterman, Jonas De Vylder, Saskia Lippens, Hiêp Q. Luong, Christopher J. Guérin, Wilfried Philips |
Editors |
Winnok H. De Vos, Sebastian Munck, Jean-Pierre Timmermans |
Abstract |
The goal of modern microscopy is to acquire high-quality image based data sets. A typical microscopy workflow is set up in order to address a specific biological question and involves different steps. The first step is to precisely define the biological question, in order to properly come to an experimental design for sample preparation and image acquisition. A better object representation allows biological users to draw more reliable scientific conclusions. Image restoration can manipulate the acquired data in an effort to reduce the impact of artifacts (spurious results) due to physical and technical limitations, resulting in a better representation of the object of interest. However, precise usage of these algorithms is necessary so as to avoid further artifacts that might influence the data analysis and bias the conclusions. It is essential to understand image acquisition, and how it introduces artifacts and degradations in the acquired data, so that their effects on subsequent analysis can be minimized. This paper provides an overview of the fundamental artifacts and degradations that affect many micrographs. We describe why artifacts appear, in what sense they impact overall image quality, and how to mitigate them by first improving the acquisition parameters and then applying proper image restoration techniques. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 9 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Professor > Associate Professor | 2 | 22% |
Researcher | 2 | 22% |
Student > Ph. D. Student | 1 | 11% |
Student > Doctoral Student | 1 | 11% |
Unknown | 3 | 33% |
Readers by discipline | Count | As % |
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Computer Science | 2 | 22% |
Biochemistry, Genetics and Molecular Biology | 1 | 11% |
Physics and Astronomy | 1 | 11% |
Unknown | 5 | 56% |