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P&S: Image-guided digital twinning of cardiac anatomy and function
Last Updated: 2026-06-01 11:33:22
Abstract
The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
Objective
Digital twins are in-silico replica of physiological systems modelling anatomy and/or function. They are increasingly being used for data augmentation of partial data, biomarkers calculation and evaluation of multiple functional conditions [1,2]. This course will provide hands-on experience on the generation of digital twins for cardiac applications. It will cover an introduction of basics concepts of cardiac biomechanics, numerical modelling and physics-informed neural networks [2,3]. In the practical part, the students will apply these concepts for the generation of a cardiac digital twin from Magnetic Resonance Imaging data. These models will be used to extract clinical indices (ejection fraction, strains, myocardial mass) and simulate physiological and pathological function. Learning objectives: Upon completion of the course students are able to: • understand physiological basis of cardiac mechanics and function and the clinical indices associated with its assessment • understand the basics of neural networks and physics-informed neural networks • build anatomical digital twins of cardiac anatomy from patient-specific magnetic resonance images • personalize cardiac functional twins using physics-informed neural networks Prerequisites: • Python • English (the course will be thought in English) References [1] Joyce, T et al. Rapid inference of personalised left-ventricular meshes by deformation-based differentiable mesh voxelization, Medical Image Analysis, 79, 102445 (2022) [2] Buoso, S., Joyce, T., and Kozerke, S. Personalising left-ventricular biophysical models of the heart using parametric physics-informed neural networks. Medical Image Analysis 71,102066 (2021) [3] Buoso, S., et al. MRXCAT2.0: Synthesis of realistic numerical phantoms by combining left-ventricular shape learning, biophysical simulations and tissue texture generation. Journal of Cardiovascular Magnetic Resonance 25, 25 (2023). Dates • Week 1 o 19th February: 14.00-16.00 o 20th February: 14.00-16.00 • Week 2 o 26th February: 14.00-16.00 o 27th February: 14.00-16.00 • Week 3 o 5th March: 14.00-16.00 o 6th March: 14.00-16.00 • Week 4 o 12th March: 14.00-16.00 o 13th March: 14.00-16.00 • Week 5 o 19th March: 14.00-16.00 o 20th March: 14.00-16.00 • Week 6 o 26th March: 14.00-16.00 o 27th March: 14.00-16.00 • Week 7 o 2nd April: 14.00-16.00 o 3rd April: 14.00-16.00
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Semesterly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
- Signup Start
- 14.02.2025
- Signup End
- 28.02.2025
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| practical/laboratory course |
P&S: Image-Guided Digital Twinning of Cardiac Anatomy and Function
Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account):
Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitagmittag im Semester möglich.
To access the offer and to enroll for courses log in (with your n.ethz account):
Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester.
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2 h weekly |
Offered In
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Praktika, Projekte, Seminare (Es müssen mindestens 15 KP aus der Kategorie "Praktika, Projekte, Seminare" erworben werden)
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Projekte & Seminare (nur für BSc EEIT) (Die Belegung ist ausschliesslich für Studierende im BSc Elektrotechnik und Informationstechnologie ab Freitag vor Semesterbeginn möglich. Plätze werden über das P&S-Bewerbungstool ( ) zugeteilt. Siehe weitere Angebote unter "Projekte & Seminare (offen für alle)".)
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