Get familiar with one of the world's most highly regarded Digital Image processors, ImageJ. This tutorial takes you through every aspect of viewing, processing, and analysing 2D, 3D, and 4D images, clearly and comprehensively.
Overview
In Detail
Digital image processing is an increasingly important field across a vast array of scientific disciplines. ImageJ’s long history and ever-growing user base makes it a perfect candidate for solving daily tasks involving all kinds of image analysis processes.
Image Processing with ImageJ is a practical book that will guide you from the most basic analysis techniques to the fine details of implementing new functionalities through the ImageJ plugin system, all of it through the use of examples and practical cases.
ImageJ is an excellent public domain imaging analysis platform that can be very easily used for almost all your image processing needs. Image Processing with ImageJ will start by showing you how to open a number of different images, become familiar with the different options, and perform simple analysis operations using the provided image samples.
You will also learn how to make modifications through ImageJ filters and how to make local measurements using the selections system. You will also find the instructions necessary to record all the steps you perform so they can be saved and re-run on the same image to ensure analysis reproducibility. Finally, you will get to know some different ImageJ plugins and will learn how to implement your own.
What you will learn from this book
Approach
The book will help readers discover the various facilities of ImageJ through a tutorial-based approach.
Who this book is written for
This book is targeted at scientists, engineers, technicians, and managers, and anyone who wishes to master ImageJ for image viewing, processing, and analysis. If you are a developer, you will be able to code your own routines after you have finished reading this book. No prior knowledge of ImageJ is expected.
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José María Mateos Pérez is a Spanish postdoctoral fellow at the Montreal Neurological Institute (http://www.mcgill.ca/neuro/), where his main research lines deal with neurodevelopment and machine learning applied to clinical prediction. He has also been an experienced ImageJ user and has developed several macros and plugins. One of them, jClustering, has been published in PLOS ONE, a peer-reviewed journal. When he has enough time to procrastinate, he also likes to develop data analysis tools in Python and R.
Javier Pascau received his PhD from Polytechnic University in Madrid in 2006 and is currently a visiting professor at Carlos III University, Madrid. He has been a part of Biomedical Imaging and Instrumentation Group, a research laboratory with a multidisciplinary team of engineers, physicists, biologists, and physicians located both in the university as well as Hospital General Universitario Gregorio Maran (biig.uc3m.es). Javier's research and teaching cover areas such as medical image processing, analysis, quantification, and multimodal registration, both in preclinical and clinical environments. He has been involved in the development of small animal PET and CT devices. In the last few years, Javier has led several projects on intraoperative radiation therapy and image-guided surgery. He has authored more than 40 papers published in peer-reviewed journals over the last 15 years.
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