Description

Book 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.

Table of 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.

Diagnostic Radiology Physics with MATLAB

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£43.69

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RRP £45.99 – you save £2.30 (5%)

Order before 4pm today for delivery by Tue 30 Dec 2025.

A Paperback by Johan Helmenkamp, Robert Bujila, Gavin Poludniowski

15 in stock


    View other formats and editions of Diagnostic Radiology Physics with MATLAB by Johan Helmenkamp

    Publisher: Taylor & Francis Ltd
    Publication Date: 5/30/2022 12:00:00 AM
    ISBN13: 9780367642624, 978-0367642624
    ISBN10: 036764262X

    Description

    Book 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.

    Table of 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.

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