Image and System Analysis
9 credits cr.
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This is an introductory course to image and system analysis aiming to provide the basic knowledge on image data processing and system analysis for medical imaging and radiotherapy optimization.
In this course you will study methods used for signal processing such as transform methods (Fourier, Laplace and Z-transform), impulse response methods, variance and differential methods and signal analysis, filtering and noise management. Methods for image visualization, segmentation and registration applied to medical images are also studied as well as statistical methods for image data analysis. The course includes classroom lectures, computer exercises and calculation exercises.
This is an advanced course given during the daytime. The course is included in the Master`s Programme in Medical Physics. I can also be taken as an independent course.
The education consists of lectures and tutorials, calculation exercises and computer exercises as well as practical demonstrations.
The course is examined through written exam.
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
Course literatureNote that the course literature can be changed up to two months before the start of the course.
Gonzalez RC, Woods, RE: Digital Image Processing, 3rd ed. Pearson, 2008
Här ligger ett skript.
When can I apply?
Registration is open from mid-March to mid-April for courses that run in the fall, and from mid-September to mid-October for courses that run in the spring.
Please note that many courses open for late registration in mid-July for courses in the autumn term and in mid-December for courses in the spring term.
Bo Sundborg, email: Bo.Sundborg@fysik.su.se
Ana Sagués Carracedo, e-mail: email@example.com
Academic advisor at the Department of Physics: firstname.lastname@example.org
Student office: email@example.com