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Computational Magnetic Resonance Imaging (Computational MRI)5 ECTS (englische Bezeichnung: Computational Magnetic Resonance Imaging)
(Prüfungsordnungsmodul: Computational Magnetic Resonance Imaging)
Modulverantwortliche/r: Florian Knoll Lehrende:
Florian Knoll, Bruno Riemenschneider
Start semester: |
WS 2021/2022 | Duration: |
1 semester | Cycle: |
jährlich (WS) |
Präsenzzeit: |
60 Std. | Eigenstudium: |
90 Std. | Language: |
Englisch |
Lectures:
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Computational Magnetic Resonance Imaging Vorlesung
(Vorlesung, 2 SWS, Florian Knoll, Mon, Thu, 10:00 - 12:00, 01.030)
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Computational Magnetic Resonance Imaging Uebung
(Übung, 2 SWS, Florian Knoll et al., Thu, 10:00 - 12:00, Raum n.V.)
Empfohlene Voraussetzungen:
It is recommended to finish the following modules before starting this module:
Medizintechnik II (Bildgebende Verfahren) (SS 2021)
Magnetic Resonance Imaging 1 (WS 2020/2021)
Inhalt:
Computational Magnetic Resonance Imaging provides a deeper look into computational and machine learning methods for the inverse problem of MRI data acquisition and image reconstruction. It is organized as a series of lectures with accompanying programming exercises. In the exercises, students will use Matlab or Python and PyTorch to implement and test the different methods discussed in class. Topics covered will include but are not limited to:
Lernziele und Kompetenzen:
After completing this course, students will be able to:
Literatur:
Z.P. Liang. Constrained Reconstruction Methods in MR Imaging.
http://mri.beckman.illinois.edu/resources/liang_1992_constrained_imaging_review.pdf D. Nishimura. Principles of Magnetic Resonance Imaging. https://www.lulu.com/en/us/shop/dwight-nishimura/principles-of-magnetic-resonance-imaging/paperback/product-1nqdq4j2.html?page=1&pageSize=4 M. Bernstein. Handbook of MRI Pulse Sequences. https://www.amazon.com/Handbook-Pulse-Sequences-Matt-Bernstein/dp/0120928612
Weitere Informationen:
Keywords: Medical Imaging, Inverse Problems, Magnetic Resonance Imaging, Machine Learning, Medizinische Bildgebung, Magnetresonanzbildgebung, Inverse Probleme
Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:
- Artificial Intelligence (Master of Science)
(Po-Vers. 2021s | TechFak | Artificial Intelligence (Master of Science) | Gesamtkonto | Nebenfach | Nebenfach Artificial Intelligence in Biomedical Engineering | Computational Magnetic Resonance Imaging)
Dieses Modul ist daneben auch in den Studienfächern "Data Science (Master of Science)", "Informatik (Master of Science)" verwendbar. Details
Studien-/Prüfungsleistungen:
Computational Magnetic Resonance Imaging (Prüfungsnummer: 31091)
- Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 2.5 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- weitere Erläuterungen:
Grade will be determined by a 30 Min oral exam at the end of the course.
- Prüfungssprache: Englisch
- Erstablegung: WS 2021/2022, 1. Wdh.: SS 2022
Computational Magnetic Resonance Imaging (Prüfungsnummer: 31092)
- Studienleistung, Übungsleistung, Dauer (in Minuten): 30, unbenotet, 2.5 ECTS
- weitere Erläuterungen:
Students can receive bonus points during the practical exercises.
- Prüfungssprache: Englisch
- Erstablegung: WS 2021/2022, 1. Wdh.: SS 2022
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