Overview
What you will study
The use of computer tools for analyzing 3D medical images has improved the diagnosis and treatment of different diseases. The 3D Image Reconstruction and Analysis in Medicine course offered by KTH Royal Institute of Technology covers the concepts, theories and most used methods for this aim, starting from obtaining readable 3D images from raw acquired data from the scanners (image reconstruction), improving their quality (image restoration and enhancement), aligning images from the same or different modality (image registration), detecting relevant regions from images (image segmentation) and extracting meaningful information from the images (image analysis). The course is focused to solve medically relevant problems.
After completing of this course, the participant will be able for each of the aforementioned problems to:- Understand the main issues and challenges
- Describe the main approaches and methods and their main differences
- Summarize pros and cons and scope of different methods
- Identify and understand the mathematical theory of the most used methods
- Develop and systematically evaluate different methods for solving simplified problems
- Use and adapt advanced tools for solving complex problems
- Select and adapt the most appropriate methods to solve problems in image reconstruction and analysis
- Analyze the effect of different parameters of the methods in particular cases
- Explain orally and in writing the proposed strategy for solving specific problems
in order to:
- understand the complete pipeline for using computational tools for image analysis in a medical context
- be able to implement computational solutions in image reconstruction and analysis to medically relevant problems
- have a broad knowledge base that can ease understanding literature in the field
Programme Structure
The program focuses on:
- Image reconstruction: different methods for tomographic reconstruction (obtaining 3D images from 2D projections) and from frequency domain acquisitions (magnetic resonance).
- Image restoration and enhancement: image filtering and enhancement in the spatial, frequency and spatial-frequency domain.
- Image registration: linear and non-linear registration and registration with prior information.
- Image segmentation: voxel-, graph-, contour- and model-based image segmentation.
- Image analysis: feature extraction, image classification, image regression, machine learning and deep learning for image analysis.
Key information
Duration
- Full-time
- 5 months
Start dates & application deadlines
- StartingApplication deadline not specified.
Language
Credits
Delivered
Disciplines
Medical Imaging View 12 other Short Courses in Medical Imaging in SwedenWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Student insurance
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- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
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Other requirements
General requirements
- Bachelor’s degree in Biomedical Engineering, Engineering Physics, Electrical Engineering, Computer Science or equivalent.
- English B/6.
Tuition Fee
Living costs for Stockholm
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.