Imaging and computing methods are key to advances and innovation in medicine. This course introduces established fundamentals as well as modern techniques and methods of imaging and computing in medicine.
Learning objective
The learning objectives include 1. Understanding and practical implementation of biosignal processes methods for imaging; 2. Understanding of imaging techniques including radiation imaging, radiographic imaging systems, computed tomography imaging, diagnostic ultrasound imaging, and magnetic resonance imaging; 3. Knowledge of computing, programming, modelling and simulation fundamentals; 4. Computational and systems thinking as well as scripting and programming skills; 5. Understanding and practical implementation of emerging computational methods and their application in medicine including artificial intelligence, deep learning, big data, and complexity; 6. Understanding of the emerging concept of personalised and in silico medicine; 7. Encouragement of critical thinking and creating an environment for independent and self-directed studying.
Content
Imaging and computing methods are key to advances and innovation in medicine. This course introduces established fundamentals as well as modern techniques and methods of imaging and computing in medicine. For the imaging portion of the course, biosignal processing, radiation imaging, radiographic imaging systems, computed tomography imaging, diagnostic ultrasound imaging, and magnetic resonance imaging are covered. For the computing portion of the course, computing, programming, and modelling and simulation fundamentals are covered as well as their application in artificial intelligence and deep learning; complexity and systems medicine; big data and personalised medicine; and computational physiology and in silico medicine. The course is structured as a seminar in three parts of 45 minutes with video lectures and a flipped classroom setup. In the first part (TORQUEs: Tiny, Open-with-Restrictions courses focused on QUality and Effectiveness), students study the basic concepts in short, interactive video lectures on the online learning platform Moodle. Students are able to post questions at the end of each video lecture or the Moodle forum that will be addressed in the second part of the lectures using a flipped classroom concept. For the flipped classroom, the lecturers may prepare additional teaching material to answer the posted questions (Q&A). Following the Q&A, the students will form small groups to acquire additional knowledge using online, python-based activities via JupyterHub or additionally distributed material and discuss their findings in teams. Learning outcomes will be reinforced with weekly Moodle assignments to be completed during the flipped classroom portion.
