| Chapter title |
Seeing Is Believing: Quantifying Is Convincing: Computational Image Analysis in Biology.
|
|---|---|
| Chapter number | 1 |
| 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_1 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-928547-4, 978-3-31-928549-8
|
| Authors |
Ivo F. Sbalzarini, Sbalzarini, Ivo F. |
| Editors |
Winnok H. De Vos, Sebastian Munck, Jean-Pierre Timmermans |
| 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 tissue-level imaging, providing pointers to the specialized literature and listing available software tools. We place particular emphasis on clear categorization of image-analysis 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. |
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|---|---|---|
| Brazil | 1 | 100% |
Demographic breakdown
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|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
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|---|---|---|
| Israel | 1 | 2% |
| Denmark | 1 | 2% |
| Sri Lanka | 1 | 2% |
| Unknown | 62 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 25% |
| Researcher | 14 | 22% |
| Student > Master | 6 | 9% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 4 | 6% |
| Other | 8 | 12% |
| Unknown | 12 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 15% |
| Biochemistry, Genetics and Molecular Biology | 9 | 14% |
| Engineering | 7 | 11% |
| Computer Science | 7 | 11% |
| Medicine and Dentistry | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 17 | 26% |