Bioimage data analysis workflows -- advanced components and methods / Kota Miura, Nataša Sladoje, editors.
2022
QH207
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Unlimited
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Open access
Details
Title
Bioimage data analysis workflows -- advanced components and methods / Kota Miura, Nataša Sladoje, editors.
ISBN
9783030763947 (electronic bk.)
3030763943 (electronic bk.)
9783030763930 (print)
3030763935
3030763943 (electronic bk.)
9783030763930 (print)
3030763935
Published
Cham : Springer, 2022.
Language
English
Description
1 online resource (x, 212 pages) : color illustrations.
Item Number
10.1007/978-3-030-76394-7 doi
Call Number
QH207
Dewey Decimal Classification
570.28/2
Summary
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.
Note
Includes index.
Access Note
Open access.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 7, 2022).
Added Author
Miura, Kota, editor.
Sladoje, Nataša, editor.
Sladoje, Nataša, editor.
Series
Learning materials in biosciences, 2509-6133
Available in Other Form
Print version: 9783030763930
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Online Access
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Table of 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.
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.