Projekt Flat-Panel CT Reconstruction (ProjFCR)
- Dozentinnen/Dozenten
- Dr.-Ing. Yixing Huang, Fabian Wagner, M. Sc., Paula Andrea Pérez-Toro, M. Sc.
- Angaben
- Praktikum
Online , ECTS-Studium, ECTS-Credits: 5, Sprache Deutsch oder Englisch, This course will be held online. No registration is required to attend this course. All further information will be provided in the StudOn course (link below).
Zeit: Do 10:00 - 12:00, 0.01-142 CIP
- Studienfächer / Studienrichtungen
- WPF INF-MA ab 1
WPF MT-MA ab 3
- Inhalt
- The aim of this master project is to build a state-of-the-art flat-panel CT reconstruction software. The project is designed in two parts: The first part is the Academic Laboratory (Hochschulpraktikum). These 5 ECTS can be earned by attending the course, finishing the exercises and giving a short presentation at the end of the semester. The second part is the 5 ECTS Research Laboratory (Forschungspraktikum), where after the semester the students can work on research topics related to the topics taught in the course.
In the Academic Laboratory, the basics of CT reconstruction will be developed in a group. All participants will create a basic CT reconstruction pipeline that is able to reconstruct flat-panel CT images.
The following topics will be taught and implemented in this course:
In the Research Laboratory, the participants will be asked to adopt the designed pipeline individually to specific problems in CT reconstruction. These topics are always related to current research at the Pattern Recognition Lab, including for example:
You will incorporate your work into a fully-fledged CT reconstruction and analysis tool that makes it easy to evaluate the reconstruction algorithms. At the end of the project, a trip to the Siemens Healthineers in Forchheim is planned in order to experiment with a real scanner. The first lecture will take place 28 April at 10:00 am via Zoom.
- ECTS-Informationen:
- Credits: 5
- Zusätzliche Informationen
- Schlagwörter: Master Project, Pattern Recognition, CT Reconstruction
Erwartete Teilnehmerzahl: 10, Maximale Teilnehmerzahl: 12
www: https://www.studon.fau.de/studon/goto.php?target=crs_4389725
- Verwendung in folgenden UnivIS-Modulen
- Startsemester SS 2022:
- Projekt Flat-Panel CT Reconstruction (ProjFCR)
- Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
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