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Make Life Visible

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ISBN: 9789811379086 Year: Pages: 292 DOI: 10.1007/978-981-13-7908-6 Language: English
Publisher: Springer Nature
Subject: Medicine (General) --- Neurology --- Biology
Added to DOAB on : 2020-02-04 11:21:23
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This open access book describes marked advances in imaging technology that have enabled the visualization of phenomena in ways formerly believed to be completely impossible. These technologies have made major contributions to the elucidation of the pathology of diseases as well as to their diagnosis and therapy. The volume presents various studies from molecular imaging to clinical imaging. It also focuses on innovative, creative, advanced research that gives full play to imaging technology in the broad sense, while exploring cross-disciplinary areas in which individual research fields interact and pursuing the development of new techniques where they fuse together. The book is separated into three parts, the first of which addresses the topic of visualizing and controlling molecules for life. Th e second part is devoted to imaging of disease mechanisms, while the final part comprises studies on the application of imaging technologies to diagnosis and therapy. Th e book contains the proceedings of the 12th Uehara International Symposium 2017, “Make Life Visible” sponsored by the Uehara Memorial Foundation and held from June 12 to 14, 2017. It is written by leading scientists in the field and is an open access publication under a CC BY 4.0 license. ;

Bioimage Data Analysis Workflows

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Book Series: Learning Materials in Biosciences ISBN: 9783030223861 Year: Pages: 170 DOI: 10.1007/978-3-030-22386-1 Language: English
Publisher: Springer Nature
Subject: Medicine (General) --- Biology
Added to DOAB on : 2020-02-04 11:21:06
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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.

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