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Sridevi Pudipeddi - Image processing and acquisition using Python

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Sridevi Pudipeddi Image processing and acquisition using Python

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Introduction to Images and Computing using Python Introduction to Python Introduction What Is Python? Python Environments Running a Python Program Basic Python Statements and Data TypesComputing using Python Modules Introduction Python Modules Numpy Scipy Matplotlib Python Imaging Library Scikits Python OpenCV ModuleImage and Its Properties Introduction Image and Its PropertiesImage TypesData Structures for Image AnalysisProgramming ParadigmImage Processing using Python Spatial Filters Introduction FilteringEdge Detection using DerivativesImage Enhancement Introduction Pixel Transformation Ima. Read more...
Abstract: Introduction to Images and Computing using Python Introduction to Python Introduction What Is Python? Python Environments Running a Python Program Basic Python Statements and Data TypesComputing using Python Modules Introduction Python Modules Numpy Scipy Matplotlib Python Imaging Library Scikits Python OpenCV ModuleImage and Its Properties Introduction Image and Its PropertiesImage TypesData Structures for Image AnalysisProgramming ParadigmImage Processing using Python Spatial Filters Introduction FilteringEdge Detection using DerivativesImage Enhancement Introduction Pixel Transformation Ima

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Image Processing and Acquisition using Python Ravishankar Chityala Sridevi - photo 1

Image Processing and Acquisition using Python

Ravishankar Chityala

Sridevi Pudipeddi

CRC Press Taylor Francis Group 6000 Broken Sound Parkway NW Suite 300 Boca - photo 2

CRC Press

Taylor & Francis Group

6000 Broken Sound Parkway NW, Suite 300

Boca Raton, FL 33487-2742

2015 by Taylor & Francis Group

CRC Press is an imprint of Taylor & Francis Group, an Informa business

No claim to original U.S. Government works

Version Date: 20150825

International Standard Book Number-13: 978-1-4987-6057-7 (EPUB)

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CHAPMAN & HALL/CRC
MATHEMATICAL AND COMPUTATIONAL
IMAGING SCIENCES

Series Editors

Chandrajit Bajaj

Center for Computational Visualization
The University of Texas at Austin

Guillermo Sapiro

Department of Electrical
and Computer Engineering
Duke University

Aims and Scope

This series aims to capture new developments and summarize what is known over the whole spectrum of mathematical and computational imaging sciences. It seeks to encourage the integration of mathematical, statistical and computational methods in image acquisition and processing by publishing a broad range of textbooks, reference works and handbooks. The titles included in the series are meant to appeal to students, researchers and professionals in the mathematical, statistical and computational sciences, application areas, as well as interdisciplinary researchers involved in the field. The inclusion of concrete examples and applications, and programming code and examples, is highly encouraged.

Published Titles

Image Processing for Cinema
by Marcelo Bertalmo

Image Processing and Acquisition using Python
by Ravishankar Chityala and Sridevi Pudipeddi

Statistical and Computational Methods in Brain Image Analysis
by Moo K. Chung

Rough Fuzzy Image Analysis: Foundations and Methodologies
by Sankar K. Pal and James F. Peters

Theoretical Foundations of Digital Imaging Using MATLAB
by Leonid P. Yaroslavsky

Proposals for the series should be submitted to the series editors above or directly to:
CRC Press, Taylor & Francis Group
3 Park Square, Milton Park, Abingdon, OX14 4RN, UK

To our parents and siblings

Foreword

I first met one of the authors, Dr. Ravishankar (Ravi) Chityala, in 2006 when he was a PhD student at the Toshiba Stroke Research Center, SUNY-Buffalo. Ravis PhD work in medical imaging was fruitful and influential, and I have been following his post-PhD career ever since. In reading this book, I was impressed by the fact that, despite Ravis current focus on computing and visualization, his knowledge of medical imaging has only deepened and expanded, which has enabled him, along with his co-author, Dr. Sridevi Pudipeddi, to write a very competent treatment of the subject of medical imaging. Thus, it is a pleasure for me to write a foreword to this very good book.

This is a book that every imaging scientist should have on his or her desk because image acquisition and processing is becoming a standard method for qualifying and quantifying experimental measurements. Moreover, I believe students and researchers need a course or a book to learn both image acquisition and image processing using a single source, and this book, as a well-rounded introduction to both topics, serves that purpose very well. The topics treated are complex, but the authors have done a great job of covering the most commonly used image acquisition modalities, such as x-ray and computed tomography, magnetic resonance imaging, and microscopes, concisely and effectively, providing a handy compendium of the most useful information.

As Confucius said, I see and I remember, I do and I understand; this book aims to provide hands-on learning that enables the reader to understand the concepts explained in the book by means of applying the various examples written in the Python code. But do not be discouraged if you have never used Python or any other script language since learning it is very straightforward. As a long-time Perl user, I had no problem installing Python and trying several useful examples from the book. Most of the equations provided in the book are accompanied by codes that can be quickly run and modified for the reader to test new ideas and apply to his or her own research.

Being a medical imaging scientist myself, I really enjoyed reading the sections on x-ray, computed tomography and magnetic resonance imaging. The authors provide a well-balanced introduction to these modalities and cover all the important aspects of image acquisition, as well as image reconstruction and artifacts correction. The authors also provide a large number of references to other books and papers for readers interested in learning more details.

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