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Table of contents

  1. Front Matter
    Pages I-X
  2. Kota Miura, Perrine Paul-Gilloteaux, Sébastien Tosi, Julien Colombelli
    Pages 1-7 Open Access
  3. Fabrice P. Cordelières, Chong Zhang
    Pages 33-66 Open Access
  4. Jean-Yves Tinevez, Sébastien Herbert
    Pages 67-96 Open Access
  5. Simon F. Nørrelykke
    Pages 97-141 Open Access
  6. Back Matter
    Pages 167-170

About this book

Introduction

This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows.

The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.


Keywords

Bioimaging Bioimage Analysis ImagJ Imaging for Biologists Learning Scripting Language Matlab Microscopy Images Python Quantitaive Analysis Quantitative Microscopy Open Access

Editors and affiliations

  • Kota Miura
    • 1
  • Nataša Sladoje
    • 2
  1. 1.Im Neuenheimer Feld 267Nikon Imaging Center Bioquant BQ 0004HeidelbergGermany
  2. 2.Department of Information TechnologyCentre for Image Analysis, Uppsala UniversityUppsalaSweden

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-22386-1
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2020
  • License CC BY
  • Publisher Name Springer, Cham
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-3-030-22385-4
  • Online ISBN 978-3-030-22386-1
  • Series Print ISSN 2509-6125
  • Series Online ISSN 2509-6133
  • Buy this book on publisher's site