Bioimage data analysis workflows /

Bioimage data analysis workflows /

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Bibliographic Details
Imprint:	Cham : Springer, 2020.
Description:	1 online resource (x, 170 pages) : illustrations (some color)
Language:	English
Series:	Learning materials in biosciences, 2509-6125 Learning materials in biosciences,
Subject:	Microscopy -- Technique. Electron microscopy. Microscopy, Electron Electron microscopy. Microscopy -- Technique.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12341485

Hidden Bibliographic Details
Other authors / contributors:	Miura, Kōta, editor. Sladoje, Nataša, editor.
ISBN:	9783030223861 3030223868 9783030223854 303022385X
Notes:	Open access. English. Online resource; title from PDF title page (SpringerLink, viewed October 25, 2019).
Summary:	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.
Other form:	303022385X
Standard no.:	10.1007/978-3-030-22386-1 10.1007/978-3-030-22

Description
Summary:	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.
Physical Description:	1 online resource (x, 170 pages) : illustrations (some color)
ISBN:	9783030223861 3030223868 9783030223854 303022385X
ISSN:	2509-6125
Access:	Open access.