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376-0022-00L 6 Credits BSC , MSC , NDS D-CHAB , D-MAVT , D-PHYS , D-HEST , D-BIOL , D-GESS , D-ITET
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Imaging and Computing in Medicine

VVZ CR 4.2

Last Updated: 2026-06-01 11:33:22

Abstract

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.

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.

Resources

Lecture Notes

Stored on Moodle.

Learning Materials (Links)

General Information

Language
English
Levels
BSC , MSC , NDS
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 120 minutes
Aids
English Dictionary
Digital
The exam takes place on devices provided by ETH Zurich.
Exams will be conducted on the computer in a session examination. Additionally, students can receive a bonus of 0.25 grade points towards the final exam grade for online participation in the interactive videos in the TORQUES. The maximum grade 6 for the lecture can also be achieved if only the session exam is completed. In the case of a possible examination repetition, the performance during the course is taken over by default. If this is not desired, the lecture must be retaken.

Course Components

Type Title Time & Place Hours
lecture with exercise Imaging and Computing in Medicine
  • Tue 13:15-16:00 (HG F 3)
  • Tue 14:15-16:00 (HG D 3.1)
  • Tue 14:15-16:00 (HG D 3.3)
  • Tue 14:15-16:00 (HG D 5.1)
  • Tue 14:15-16:00 (HG D 5.3)
  • Tue 14:15-16:00 (HG F 26.5)
4 h weekly

Offered In