Description of Individual Course Units
|
Offered By |
Graduate School of Natural and Applied Sciences |
Level of Course Unit |
Second Cycle Programmes (Master's Degree) |
Course Coordinator |
PROFESSOR DOCTOR MUSTAFA ALPER SELVER |
Offered to |
Industrial Ph.D. Program In Advanced Biomedical Technologies |
Course Objective |
Magnetic Resonance Imaging (MR) is an exciting new source of diagnostic information. The technique utilizes strong magnets and low energy radio frequency signals to gather information from certain atomic nuclei within the body. These signals are used to electronically create images of internal anatomy. The resulting magnetic pictures are, in some ways, similar to X-ray images, but the process does not require ionizing radiation. This course will describe the fundamental principles of MR, how to generate the signals and form images, and how to manipulate different MR parameters to provide maximum diagnostic information |
Learning Outcomes of the Course Unit |
||||||||||
|
Mode of Delivery |
Face -to- Face |
Prerequisites and Co-requisites |
None |
Recomended Optional Programme Components |
None |
Course Contents |
|||||||||||||||||||||||||||||||||||||||||||||
|
Recomended or Required Reading |
TEXTBOOK : Zhi-Pei Liang and Paul C. Lauterbur, Principles of |
Planned Learning Activities and Teaching Methods |
The course is taught in a lecture, class presentation and discussion format. All class members are expected to attend the lecture hours and take part in the discussions. Besides the taught lecture, some group or individual presentations are to be prepared by the students and presented. In addition, homeworks and quizzes will be given to the students. |
Assessment Methods |
||||||||||||||||
|
Further Notes About Assessment Methods |
None |
Assessment Criteria |
- Homework(s) |
Language of Instruction |
English |
Course Policies and Rules |
To be announced. |
Contact Details for the Lecturer(s) |
alper.selver@deu.edu.tr |
Office Hours |
To be announced. |
Work Placement(s) |
None |
Workload Calculation |
||||||||||||||||||||||||||||||||||||
|
Contribution of Learning Outcomes to Programme Outcomes |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|