Diagnostic Radiology Physics with MATLAB®
A Problem-Solving Approach
Herausgeber: Poludniowski, Gavin; Bujila, Robert; Helmenkamp, Johan
Diagnostic Radiology Physics with MATLAB®
A Problem-Solving Approach
Herausgeber: Poludniowski, Gavin; Bujila, Robert; Helmenkamp, Johan
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Traditionally, computer programming skills have rarely been emphasized during the education and training of medical physicists, meaning that many individuals enter the workplace without the ability to solve real-world clinical problems.
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Traditionally, computer programming skills have rarely been emphasized during the education and training of medical physicists, meaning that many individuals enter the workplace without the ability to solve real-world clinical problems.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Series in Medical Physics and Biomedical Engineering
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 292
- Erscheinungstermin: 30. Mai 2022
- Englisch
- Abmessung: 177mm x 254mm x 28mm
- Gewicht: 694g
- ISBN-13: 9780367642624
- ISBN-10: 036764262X
- Artikelnr.: 64105561
- Series in Medical Physics and Biomedical Engineering
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 292
- Erscheinungstermin: 30. Mai 2022
- Englisch
- Abmessung: 177mm x 254mm x 28mm
- Gewicht: 694g
- ISBN-13: 9780367642624
- ISBN-10: 036764262X
- Artikelnr.: 64105561
Johan Helmenkamp, M.Sc. Johan obtained his Master's degree in Medical Radiation Physics at Lund University (Sweden) in 2010. Johan is a practising medical physics expert in Radiology at the Karolinska University Hospital (Sweden) and teaches undergraduate medical physics students, radiology residents and radiographers in topics such as imaging physics and technology, image processing and radiation safety. Johan has chaired a course committee for a national programming course aimed at improving the programming skills of fellow medical physicists and finds MATLAB programming a necessity both as a teaching tool but also for his everyday physics practice in the clinic, where there is a high demand for accurate and well-presented data for decision making. Robert Bujila, Ph.D. Robert earned his Master's degree in Medical Radiation Physics at Stockholm University (Sweden) in 2010. After receiving his Master's degree in Medical Physics, Robert worked at the Karolinska University Hospital between 2010 and 2019 with a focus on Computed Tomography. While working as a clinical Medical Physicist, Robert received his PhD in Physics from the Royal Institute of Technology in Stockholm, Sweden with a project related to the optimization of image quality and radiation dose in CT. From the beginning of Robert's career, he has been involved in many projects that require programming where MATLAB has been an essential tool. As such, Robert understands the potential that good programming skills can provide and has been an advocate for the increased utilization of programming to forward the Medical Physics profession. During the course of editing this book, Robert has moved on from the Karolinska University Hospital to take an active role in the development of Computed Tomography systems in the private sector. Gavin Poludniowski, Ph.D. Gavin Poludniowski graduated with a PhD in Theoretical Physics from the University of Manchester (UK) in 2003. He gained his Master's degree in Medical Physics the next year from the University of Leeds, before completing the Basic Clinical Training scheme at the Regional Medical Physics Department in the North East of England. After research stints at the Royal Marsden Hospital and the University of Surrey, he moved to Sweden, where he is currently employed at the Karolinska University Hospital. Gavin has had a varied career, but for a long time a strong focus has been on research in medical imaging. His software such as "SpekCalc" and "SpekPy" have proved popular and have been used in many hospitals and research institutions around the world. He first used MATLAB before "Y2K" and still makes use of it in his work today. Gavin has also contributed previously to a book published by CRC Press (Handbook of X-ray Imaging: Physics and Technology edited by Paolo Russo).
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.
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.
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.
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.