Coordinator
Dr.ir. R. Deckers (Roel)
Contact
Dr.ir. R. Deckers (Roel) r.deckers-2@umcutrecht.nl
Faculty
Dr.ir. Roel Deckers, Dr.ir. Wilbert Bartels, Dr. Clemens Bos
Guest-lecturers: dr. Klazina Kooiman (Erasmus MC), dr. Guillaume Lajoinie (UTwente), dr. Rik Vos (TU Delft/Erasmus MC), dr. Manon Braat (UMC Utrecht), dr. Martijn Boomsma (Isala klinieken, Zwolle), prof. Dr. Jurgen Fütterer (Radboud UMC), Dr. Joan Vidal-Jové (Institut Khuab, Barcelona), prof. dr. Alessandro Napoli (Sapienza, University of Roma), Dr. Raúl Martínez-Fernández (HM CINAC, Fundación HM Hospitales de Madrid)
Date
February – April (Period 3) for the schedule please check the website of the Master’s programme Medical Imaging.
Register by sending an e-mail to r.allebrandi@umcutrecht.nl. Please note: this course may be taught partly online in Teams and partly onsite. To access the Teams account you need a solis id. If you do not yet have one, apply for one on time.
Location
University Medical Center Utrecht
Course Content
Image-guided therapeutic ultrasound is an early-stage, non-invasive therapeutic technology with the potential to transform the treatment of many medical disorders by using ultrasonic energy to target tissue deep in the body without incisions or radiation.
After this course, students will be familiar with theory and practise of various medical applications of image-guided therapeutic ultrasound. In several (guest) lectures the following topics will be covered:
• The physics and the mechanisms of ultrasound for therapeutic applications
• Ultrasound induced bio-effects
• (Medical) imaging techniques to control therapeutic ultrasound interventions
• Overview of medical conditions that can be treated with therapeutic ultrasound
Subsequently, the students will work in small groups on a practical assignment to get hands-on experience with image-guided therapeutic ultrasound.
Upon completion of the course the participant:
- will be familiar with the concepts of machine learning and deep learning
- will be familiar with the latest developments and clinical applications of these techniques
- has a basic understanding of neural networks for medical image analysis
Credit
You will be awarded 2.5 EC with a final grade ≥5.5.
Examination
The final grade consists of 3 parts:
Presentation: 45%
Report: 45%
Active participation: 10%
Literature
Handouts