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Development of Machine Learning Methods for Radiation Protection and Medical Imaging
The number of interventional procedures has been increasing because of the numerous benefits for the patient, the significant technological development and the number of operators performing procedures outside the traditional radiology department. However, exposure to ionizing radiation may have detrimental health effects to both operators and patients. Longer and more complex fluoroscopic procedures are associated with tissue reactions such as skin erythema, epilation or cataract. The radiation exposure depends on clinical factors (patient size, number of stents, tortuosity of blood vessels, etc.) as well as geometrical factors such as the image projection and table position. Machine learning methods can be used to determine which factors contribute to the radiation exposure in order to provide valuable advice to the operators to optimize the procedure.
Keywords: machine learning, interventional procedures, clinical use of x-rays, radiation protection
You have a technical background (computer science, physics, or engineering) and ideally previous experience with machine learning algorithms. Basic knowledge of Python or R is a must. Or you have a medical background and interest to determine and investigate clinical factors that affect radiation exposure during interventional procedures. Interest and motivation to work with many clinical images in a multi-disciplinary team are essential.
You have a technical background (computer science, physics, or engineering) and ideally previous experience with machine learning algorithms. Basic knowledge of Python or R is a must. Or you have a medical background and interest to determine and investigate clinical factors that affect radiation exposure during interventional procedures. Interest and motivation to work with many clinical images in a multi-disciplinary team are essential.
In this project, the candidate will participate in investigating, optimizing, and developing machine learning algorithms for radiation dose analysis.
In this project, the candidate will participate in investigating, optimizing, and developing machine learning algorithms for radiation dose analysis.
Dr. Elina Samara, elenitheano(dot)samara(at)usz(dot)ch
Dr. Elina Samara, elenitheano(dot)samara(at)usz(dot)ch