Seeing is believing: Quantifying is convincing: Computational image analysis in biology

Research output: Contribution to book/conference proceedings/anthology/reportChapter in book/anthology/reportContributedpeer-review

Contributors

Abstract

Imaging is center stage in biology. Advances in microscopy and labeling techniques have enabled unprecedented observations and continue to inspire new developments. Efficient and accurate quantification and computational analysis of the acquired images, however, are becoming the bottleneck. We review different paradigms of computational image analysis for intracellular, single-cell, and tissuelevel imaging, providing pointers to the specialized literature and listing available software tools. We place particular emphasis on clear categorization of imageanalysis frameworks and on identifying current trends and challenges in the field. We further outline some of the methodological advances that are required in order to use images as quantitative scientific measurements.

Details

Original languageEnglish
Title of host publicationFocus on Bio-Image Informatics
EditorsWinnok H. De Vos, Sebastian Munck, Jean-Pierre Timmermans
PublisherSpringer Science and Business Media B.V.
Pages1-39
Number of pages39
ISBN (electronic)978-3-319-28549-8
ISBN (print)978-3-319-28547-4
Publication statusPublished - 21 May 2016
Peer-reviewedYes

Publication series

SeriesAdvances in Anatomy Embryology and Cell Biology
Volume219
ISSN0301-5556

External IDs

Scopus 84976407823
ORCID /0000-0003-4414-4340/work/142252136

Keywords

Keywords

  • Point Spread Function, Markov Random Field, Imaging Model, Uncertainty Quantification, Evidence Theory