Diagnostic Radiology Physics with MATLAB®: A Problem-Solving Approach

✍ Scribed by Johan Helmenkamp (editor), Robert Bujila (editor), Gavin Poludniowski (editor)

• Publisher: CRC Press
• Year: 2020
• Tongue: English
• Leaves: 292
• Series: Series in Medical Physics and Biomedical Engineering
• Edition: 1
• Category: Library

✦ Synopsis

Imaging modalities in radiology produce ever-increasing amounts of data which need to be displayed, optimized, analyzed and archived: a "big data" as well as an "image processing" problem. Computer programming skills are rarely emphasized during the education and training of medical physicists, meaning that many individuals enter the workplace without the ability to efficiently solve many real-world clinical problems.

This book provides a foundation for the teaching and learning of programming for medical physicists and other professions in the field of Radiology and offers valuable content for novices and more experienced readers alike.

It focuses on providing readers with practical skills on how to implement MATLAB® as an everyday tool, rather than on solving academic and abstract physics problems. Further, it recognizes that MATLAB is only one tool in a medical physicist’s toolkit and shows how it can be used as the "glue" to integrate other software and processes together. Yet, with great power comes great responsibility. The pitfalls to deploying your own software in a clinical environment are also clearly explained. This book is an ideal companion for all medical physicists and medical professionals looking to learn how to utilize MATLAB in their work.

Features

• Encompasses a wide range of medical physics applications in diagnostic and interventional radiology
• Advances the skill of the reader by taking them through real-world practical examples and solutions with access to an online resource of example code
• The diverse examples of varying difficulty make the book suitable for readers from a variety of backgrounds and with different levels of programming experience.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Dedication
Contents
SECTION I: General topics
CHAPTER 1: The role of programming in healthcare
1.1. WHAT PROGRAMMING CAN DO FOR YOU
1.2. WHAT PROGRAMMING CAN DO FOR YOUR CLINIC: CHANGE THE NATURE OF ROUTINE WORK
1.3. WHAT PROGRAMMING CAN DO FOR YOUR CLINIC: ENABLE RESEARCH AND INNOVATION
1.4. WITH GREAT POWER COMES GREAT RESPONSIBILITY
1.5. CONCLUSION
CHAPTER 2: MATLAB fundamentals
2.1. INTRODUCTION
2.2. VARIABLES AND DATA TYPES
2.3. ARRAYS AND MATRIX MANIPULATION
2.4. MORE DATA TYPES
2.5. CONDITIONAL OPERATORS AND LOGICAL INDEXING
2.6. CONTROL FLOW
2.7. USER-DEFINED FUNCTIONS
2.8. DATA ANALYSIS
2.9. VISUALIZATION
2.10. HANDLING BIG DATA SETS
2.11. CLASSES
2.12. IMPROVING CODE PERFORMANCE
2.13. EXERCISE—BASIC IMAGE PROCESSING
2.14. CONCLUSION
CHAPTER 3: Data sources in medical imaging
3.1. INTRODUCTION
3.2. THE DICOM STANDARD AND FILE FORMAT
3.3. OTHER DATA SOURCES
3.4. CONCLUSION
CHAPTER 4: Importing, manipulating and displaying DICOM data in MATLAB
4.1. INTRODUCTION
4.2. IMPORTING IMAGE DATA
4.3. WRITING AND ANONYMIZING DICOM DATA
4.4. VISUALIZATION
4.5. CONCLUSION
CHAPTER 5: Creating automated workfows using MATLAB
5.1. INTRODUCTION
5.2. MANUAL CALCULATION OF SNR
5.3. AUTOMATING THE SNR CALCULATION USING MATLAB
5.4. CONCLUSION
CHAPTER 6: Integration with other programming languages and environments
6.1. INTRODUCTION
6.2. WHEN TO USE OTHER PROGRAMMING LANGUAGES AND ENVIRONMENTS
6.3. SYSTEM COMMANDS
6.4. INTEGRATING WITH JAVA
6.5. INTEGRATING WITH PYTHON
6.6. INTEGRATING WITH THE .NET FRAMEWORK
6.7. CONCLUSION
CHAPTER 7: Good programming practices
7.1. WHAT MAKES A GOOD PROGRAM
7.2. GOOD PRACTICES
7.3. CONCLUSION
CHAPTER 8: Sharing software
8.1. POTENTIAL OF CROWD-SOURCING
8.2. SHARE CODE USING MATLAB FILE EXCHANGE
8.3. SHARE CODE USING OTHER SOURCE-CODE HOSTING SITES
8.4. CHOOSING THE OPTIMAL APPROACH: GUI OR NOT?
8.5. BUILDING AN APP IN MATLAB
8.6. CREATING EXECUTABLES WITH THE MATLAB COMPILER
8.7. LICENSES
8.8. CONCLUSION
CHAPTER 9: Regulatory considerations when deploying your software in a clinical environment
9.1. MEDICAL DEVICE REGULATIONS
9.2. HEALTH INFORMATION PRIVACY
SECTION II: Problem-solving: examples from the trenches
CHAPTER 10: Applying good software development processes in practice
10.1. INTRODUCTION
10.2. THE TRENCH IN QUESTION: RADIOCHROMIC FILM DOSIMETRY
10.3. AN IN-HOUSE SOFTWARE VALIDATION CHECKLIST
10.4. BEFORE WRITING THE CODE
10.5. WHILE WRITING THE CODE
10.6. AFTER WRITING THE CODE
10.7. SUMMARY OF VALIDATION PROCESS AND OUTCOMES
10.8. REGARDING CERTIFICATION
10.9. CONCLUSION
CHAPTER 11: Automating quality control tests and evaluating ATCM in computed tomography
11.1. INTRODUCTION
11.2. ANALYZING CT PHANTOM IMAGES
11.3. APPLICATIONS IN CONSTANCY TESTS
11.4. APPLICATIONS IN AUTOMATIC TUBE CURRENT MODULATION
11.5. CONCLUSIONS
CHAPTER 12: Parsing and analyzing Radiation Dose Structured Reports
12.1. INTRODUCTION
12.2. STRUCTURE OF RDSR OBJECTS
12.3. PARSING RDSR OBJECTS
12.4. ANALYZING PARSED RDSR DATA
12.5. CONCLUSIONS
CHAPTER 13: Methods of determining patient size surrogates using CT images
13.1. INTRODUCTION
13.2. STRUCTURE OF THE CODE
13.3. CALCULATING SIZE METRICS FROM CT AXIAL IMAGES
13.4. CALCULATING THE SIZE-SPECIFIC DOSE ESIMATE
13.5. CONCLUSION
CHAPTER 14: Reconstructing the geometry of x-ray interventions
14.1. INTRODUCTION
14.2. ELEMENTARY VECTOR ALGEBRA
14.3. RECONSTRUCTING THE PATIENT-BEAM ALIGNMENT
14.4. RECONSTRUCTING THE SOURCE-TO-SURFACE DISTANCE
14.5. CALCULATING THE INCIDENT AIR KERMA
14.6. CONCLUSION
CHAPTER 15: Mammography and breast tomosynthesis simulation using Perlin noise
15.1. INTRODUCTION
15.2. GENERATING THE NOISE
15.3. FRACTAL NOISE
15.4. PRE-GENERATION
15.5. THE FINAL TISSUE MODEL
15.6. CONCLUSION: GENERATING BREAST TISSUE
CHAPTER 16: xrTk: a MATLAB toolkit for x-ray physics calculations
16.1. INTRODUCTION
16.2. OPTIMIZING IMAGE QUALITY
16.3. DISCUSSION
16.4. CONCLUSIONS
CHAPTER 17: Automating daily QC for an MRI scanner
17.1. INTRODUCTION
17.2. AUTOMATIC ANALYSIS OF QUALITY CONTROL IMAGES
17.3. THE MAIN FUNCTION
17.4. CONCLUSION
CHAPTER 18: Image processing at scale by containerizing’ MATLAB
18.1. INTRODUCTION
18.2. IMPROVED DICOM SUPPORT BY MATLAB-JAVA INTEGRATION
18.3. RUNNING MATLAB IN A CONTAINER
18.4. EXAMPLE PROBLEM FOR CONTAINERIZATION
18.5. XNAT: ORCHESTRATING THE IMAGE ANALYSIS OF LARGE PATIENT COHORTS
18.6. CONCLUSION
CHAPTER 19: Estimation of arterial wall movements
19.1. THE LONGITUDINAL MOVEMENT OF THE ARTERIAL WALL
19.2. BLOCK MATCHING
19.3. ARTERIAL WALL MOVEMENT MEASUREMENTS
19.4. CONCLUDING REMARKS
CHAPTER 20: Importation and visualization of ultrasound data
20.1. INTRODUCTION TO ULTRASOUND DATA
20.2. STRUCTURE OF A DATA FILE
20.3. READ DATA INTO MATLAB
20.4. GENERATING AND VISUALIZING B-MODE IMAGES
20.5. CONCLUSION
Index