Module ME4411 T

Duration

1 Semester

Turnus of offer

each winter semester

Credit points

3

Course of studies, specific fields and terms:

• Master CLS 2023, Module part of a compulsory module, MML with specialization in Image Processing
• Master MES 2020, Module part of a compulsory module, medical engineering science
• Master Entrepreneurship in Digital Technologies 2020, module part, Module part
• Master CLS 2016, Module part of a compulsory module, MML with specialization in Image Processing
• Master Computer Science 2014, module part, Module part
• Master Medical Informatics 2014, module part, Module part
• Master Entrepreneurship in Digital Technologies 2014, module part, Module part
• Master MES 2014, Module part of a compulsory module, medical engineering science

Classes and lectures:

• Computed Tomography (lecture, 2 SWS)

Workload:

• 40 hours private studies
• 35 hours in-classroom work
• 15 hours exam preparation

Contents of teaching:

• Signal processing (recapitulation of fundamental principles in signal processing)
• Mathematical methods in image reconstruction and signal processing
• X-Ray (fundamental principles, quantum statistics)
• Computed Tomography * devices, * current and past technology, * signal processing, * Fourier-based 2D and 3D image reconstruction, * algebraic and statistical image reconstruction, * image artifacts, * technical and clinical applications, * dose.

Qualification-goals/Competencies:

• Students are able to create an overview of the signal chain for medical imaging.
• They are able to explain the mathematical background for the reconstruction of CT images.
• They are able to explain the basics for the creation of X-ray.
• They are able to list all generations of CT devices and explain differences and advances.
• They are able to apply the Fourier transform.
• They are able to explain the mathematical basics for the two-dimensional image reconstruction.
• They are able to create and apply an algebraic approach for the reconstruction of CT images.
• They are able to create and apply an statistical approach for the reconstruction of CT images.
• They are able to outline the differences between two dimensional and three dimensional image reconstruction.
• They are able to transfer methods from two dimensional to three dimensional image reconstruction.

Grading through:

• Oral examination

Responsible for this module:

• Siehe Hauptmodul

Teacher:

• Institute of Medical Engineering
• Prof. Dr. rer. nat. Thorsten Buzug

Literature:

• T. M. Buzug : Computed Tomography, From Photon Statistics to Modern Cone Beam CT Springer-Verlag, Berlin/Heidelberg, 2008
• T. M. Buzug : Einführung in die Computertomographie, Mathematisch-physikalische Grundlagen der Bildrekonstruktion Springer-Verlag, Berlin/Heidelberg, 2004

Language:

• German and English skills required

Notes:

Last Updated:

02.02.2022