Full Description
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.
Contents
1. The role of programming in healthcare. 2. MATLAB fundamentals. 3. Data Sources in Medical Imaging. 4. Importing, manipulating, and displaying DICOM data in MATLAB. 5. Creating automated Creating automated. 6. Integration with other programming languages and environments. 7. Good programming practices. 8. Sharing software. 9. Regulatory considerations when deploying your software in a clinical environment. 10. Applying good software development processes in practice. 11. Automating quality control tests and evaluating ATCM in computed tomography. 12. Parsing and analyzing Radiation Dose Structured Reports. 13. Method of determining patient size surrogates using CT images. 14. Reconstructing the exposure geometry in x-ray angiography and interventional radiology. 15. Simulation of anatomical structure in mammography and breast tomosynthesis using Perlin noise. 16. xrTk: a MATLAB toolkit for x-ray physics calculations. 17. Automating daily QC for an MRI scanner. 18. Image processing at scale by containerizing MATLAB. 19. Estimation of arterial wall movements. 20. Importation and visualisation of ultrasound data.
