Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / / edited by Kota Miura, Nataša Sladoje.
This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. Addressing the main challenges in image data analysis, where acquisition by powerful imaging devices results in very large amounts of c...
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Superior document: | Learning Materials in Biosciences, |
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Place / Publishing House: | Cham : : Springer International Publishing :, Imprint: Springer,, 2022. |
Year of Publication: | 2022 |
Edition: | 1st ed. 2022. |
Language: | English |
Series: | Learning Materials in Biosciences,
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Physical Description: | 1 online resource (X, 212 p. 265 illus. in color.) |
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Miura, Kota edt Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / edited by Kota Miura, Nataša Sladoje. 1st ed. 2022. Cham Springer Nature 2022 Cham : Springer International Publishing : Imprint: Springer, 2022. 1 online resource (X, 212 p. 265 illus. in color.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Learning Materials in Biosciences, 2509-6133 Open access Unrestricted online access star This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. Addressing the main challenges in image data analysis, where acquisition by powerful imaging devices results in very large amounts of collected image data, the book discusses techniques relying on batch and GPU programming, as well as on powerful deep learning-based algorithms. In addition, downstream data processing techniques are introduced, such as Python libraries for data organization, plotting, and visualizations. Finally, by studying the way individual unique ideas are implemented in the workflows, readers are carefully guided through how the parameters driving biological systems are revealed by analyzing image data. These studies include segmentation of plant tissue epidermis, analysis of the spatial pattern of the eye development in fruit flies, and the analysis of collective cell migration dynamics. The presented content extends the Bioimage Data Analysis Workflows textbook (Miura, Sladoje, 2020), published in this same series, with new contributions and advanced material, while preserving the well-appreciated pedagogical approach adopted and promoted during the training schools for bioimage analysis organized within NEUBIAS – the Network of European Bioimage Analysts. This textbook is intended for advanced students in various fields of the life sciences and biomedicine, as well as staff scientists and faculty members who conduct regular quantitative analyses of microscopy images. Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration. Open Access English Cytology. Bioinformatics. Imaging systems in biology. Cell Biology. Computational and Systems Biology. Biological Imaging. Microscòpia electrònica thub Llibres electrònics thub Analyzing Image Data in Biology Building a Bioimage Analysis Workflow Computational Analysis Chosing the Correct Components for Given Biological Questions Data Handling and Plotting Deep Learning Fast Computation GPU-Acceleration Handling Biological data Machine Learning Phyton Processing Language Understanding Bioimage Analysis Software 3-030-76393-5 Miura, Kota. editor. edt http://id.loc.gov/vocabulary/relators/edt Sladoje, Nataša. editor. edt http://id.loc.gov/vocabulary/relators/edt |
language |
English |
format |
eBook |
author2 |
Miura, Kota. Miura, Kota. Sladoje, Nataša. Sladoje, Nataša. |
author_facet |
Miura, Kota. Miura, Kota. Sladoje, Nataša. Sladoje, Nataša. |
author2_variant |
k m km k m km k m km n s ns n s ns |
author2_role |
HerausgeberIn HerausgeberIn HerausgeberIn HerausgeberIn |
author_sort |
Miura, Kota. |
title |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / |
spellingShingle |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / Learning Materials in Biosciences, Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration. |
title_full |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / edited by Kota Miura, Nataša Sladoje. |
title_fullStr |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / edited by Kota Miura, Nataša Sladoje. |
title_full_unstemmed |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / edited by Kota Miura, Nataša Sladoje. |
title_auth |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / |
title_new |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / |
title_sort |
bioimage data analysis workflows ‒ advanced components and methods / |
series |
Learning Materials in Biosciences, |
series2 |
Learning Materials in Biosciences, |
publisher |
Springer Nature Springer International Publishing : Imprint: Springer, |
publishDate |
2022 |
physical |
1 online resource (X, 212 p. 265 illus. in color.) |
edition |
1st ed. 2022. |
contents |
Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration. |
isbn |
3-030-76394-3 3-030-76393-5 |
issn |
2509-6133 |
callnumber-first |
Q - Science |
callnumber-subject |
QH - Natural History and Biology |
callnumber-label |
QH573-671 |
callnumber-sort |
QH 3573 3671 |
genre |
Llibres electrònics thub |
genre_facet |
Llibres electrònics |
illustrated |
Not Illustrated |
dewey-hundreds |
500 - Science |
dewey-tens |
570 - Life sciences; biology |
dewey-ones |
571 - Physiology & related subjects |
dewey-full |
571.6 |
dewey-sort |
3571.6 |
dewey-raw |
571.6 |
dewey-search |
571.6 |
oclc_num |
1346984629 |
work_keys_str_mv |
AT miurakota bioimagedataanalysisworkflowsadvancedcomponentsandmethods AT sladojenatasa bioimagedataanalysisworkflowsadvancedcomponentsandmethods |
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carrierType_str_mv |
cr |
hierarchy_parent_title |
Learning Materials in Biosciences, |
is_hierarchy_title |
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / |
container_title |
Learning Materials in Biosciences, |
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