MATLAB Programming for Biomedical Engineers and Scientists

2nd Edition - May 24, 2022
Authors: Andrew P. King, Paul Aljabar
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 8 5 7 7 3 - 4
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 8 4 5 7 - 7

MATLAB Programming for Biomedical Engineers and Scientists, Second Edition provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. The book… Read more

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MATLAB Programming for Biomedical Engineers and Scientists, Second Edition provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. The book explains the principles of good programming practice, while also demonstrating how to write efficient and robust code that analyzes and visualizes biomedical data. Aimed at the biomedical engineering student, biomedical scientist and medical researcher with little or no computer programming experience, this is an excellent resource for learning the principles and practice of computer programming using MATLAB.

The book enables the reader to analyze problems and apply structured design methods to produce elegant, efficient and well-structured program designs, implement a structured program design in MATLAB, write code that makes good use of MATLAB programming features, including control structures, functions and advanced data types, and much more.

Cover image
Title page
Table of Contents
Copyright
Dedication
Quotes
About the authors
Preface
Aims and motivation
Learning objectives
What's new in the second edition?
How to use this book
Acknowledgments
References
Chapter 1: Introduction to computer programming and MATLAB®
1.1. Introduction
1.2. Computers and computer programming
1.3. MATLAB
1.4. The MATLAB environment
1.5. Help
1.6. Variables, arrays, and simple operations
1.7. Matrices
1.8. Data types
1.9. Loading and saving data
1.10. Visualizing data
1.11. Curve fitting
1.12. MATLAB scripts
1.13. Comments
1.14. Debugging
1.15. Summary
1.16. Further resources
1.17. Exercises
References
Chapter 2: Control structures
2.1. Introduction
2.2. Conditional Image 1 statements
2.3. Comparison/logical operators
2.4. Conditional Image 2 statements
2.5. Iteration: Image 3 loops
2.6. Iteration: Image 4 loops
2.7. A note about efficiency
2.8. Image 5 and Image 6
2.9. Nesting control structures
2.10. Summary
2.11. Further resources
2.12. Exercises
References
Chapter 3: Basic data types
3.1. Introduction
3.2. What is a data type?
3.3. Numeric types
3.4. The Boolean data type
3.5. Characters and character arrays
3.6. Identifying the type of a variable
3.7. Converting between types
3.8. Summary
3.9. Further resources
3.10. Exercises
Chapter 4: Functions
4.1. Introduction
4.2. Functions
4.3. Checking for errors
4.4. Function m-files and script m-files
4.5. The Image 70 keyword
4.6. A function m-file can contain more than one function
4.7. Script m-files and functions
4.8. m-files and the MATLAB search path
4.9. Naming rules
4.10. Scope of variables
4.11. Recursion: a function calling itself
4.12. Summary
4.13. Further resources
4.14. Exercises
References
Chapter 5: Program development and testing
5.1. Introduction
5.2. Incremental development
5.3. Are we finished? Validating user input
5.4. Debugging a function
5.5. Common reasons for errors when running a script or a function
5.6. Error handling
5.7. Summary
5.8. Further resources
5.9. Exercises
References
Chapter 6: Advanced data types
6.1. Introduction
6.2. Cells and cell arrays
6.3. Structures
6.4. Categorical arrays
6.5. Tables
6.6. Maps
6.7. Conversion of advanced data types
6.8. Summary
6.9. Further resources
6.10. Exercises
Chapter 7: File input/output
7.1. Introduction
7.2. Recap on basic input/output functions
7.3. Simple functions for dealing with text files
7.4. Reading from files
7.5. Writing to files
7.6. Summary
7.7. Further resources
7.8. Exercises
Chapter 8: Program design
8.1. Introduction
8.2. Top-down design
8.3. Bottom-up design
8.4. A combined approach
8.5. Alternative design approaches
8.6. Summary
8.7. Further resources
8.8. Exercises
Chapter 9: Visualization
9.1. Introduction
9.2. Visualization
9.3. Summary
9.4. Further resources
9.5. Exercises
Chapter 10: Code efficiency
10.1. Introduction
10.2. Time and memory efficiency
10.3. Tips for improving time-efficiency
10.4. Recursive and dynamic programming
10.5. Dynamic programming to improve performance
10.6. Summary
10.7. Further resources
10.8. Exercises
References
Chapter 11: Signal and image processing
11.1. Introduction
11.2. Storing and reading 1-D signals
11.3. Processing 1-D signals
11.4. Convolution
11.5. Storing and reading image data
11.6. Accessing images in MATLAB
11.7. Image processing
11.8. Image filtering
11.9. Summary
11.10. Further resources
11.11. Exercises
Chapter 12: Graphical user interfaces
12.1. Introduction
12.2. Building a graphical user interface in MATLAB
12.3. Building an app: recap
12.4. An app for image processing
12.5. Summary
12.6. Further resources
12.7. Exercises
Chapter 13: Statistics
13.1. Introduction
13.2. Descriptive statistics
13.3. Inferential statistics
13.4. Summary
13.5. Further resources
13.6. Exercises
References
Chapter 14: Machine learning
14.1. Introduction
14.2. Artificial intelligence, machine learning, and deep learning
14.3. Types of machine learning
14.4. Evaluating machine learning models
14.5. Overfitting and underfitting
14.6. Unsupervised learning
14.7. Supervised learning
14.8. Deep learning
14.9. Summary
14.10. Further resources
14.11. Exercises
References
Chapter 15: Engineering mathematics
15.1. Introduction
15.2. Scalars and vectors
15.3. Complex numbers
15.4. Matrices
15.5. Calculus
15.6. Differential equations
15.7. Summary and further resources
15.8. Exercises
References
References
References
Index

Andrew P. King

Dr King has over 20 years of experience of teaching computing courses at university level. He is currently a Reader in the Biomedical Engineering department at King's College London. With Paul Aljabar, he designed and developed the Computer Programming module for Biomedical Engineering students upon which this book was based. The module has been running since 2014 and Andrew still co-organises and teaches on it. Between 2001-2005, Andrew worked as an Assistant Professor in the Computer Science department at Mekelle University in Ethiopia, and was responsible for curriculum development, and design and delivery of a number of computing modules. Andrew's research interests focus mainly on the use of machine learning and artificial intelligence techniques to tackle problems in medical imaging, with a special focus on dynamic imaging data, i.e. moving organs (Google Scholar: https://goo.gl/ZZGrGr, group web site: http://kclmmag.org).

Affiliations and expertise

Reader in Medical Image Analysis, School of Biomedical Engineering and Imaging Science, King's College London.

Paul Aljabar

Paul Aljabar is a mathematician who enjoys using computer programming to address health and biomedical problems. He taught high school mathematics in London for twelve years before taking up a research career. Since then, his work has focused on the analysis of large collections of medical images for a range of applications, for example in order to build anatomical atlases or distinguish normal from pathological physiology. As described above, Paul and Andrew developed this book and learning materials together while teaching Biomedical Engineering undergraduates. Paul has taught on a range of undergraduate and graduate programmes focusing on the analysis and interpretation of medical and biomedical data, carried out through modelling, programming, and the application of methods that are also used in his research (Google Scholar: https://goo.gl/jAgPru).

Affiliations and expertise

Head of Imaging Science, Perspectum Ltd.