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.
