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Medical Image Analysis, 6 credits
Medicinsk bildanalys, 6 hp
TBMI02
Main field of study
Electrical Engineering Biomedical EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Hans KnutssonDirector of studies or equivalent
Linda RattfältEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Electrical Engineering, Biomedical EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Information Technology, M Sc in Engineering
- Computer Science and Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Biomedical Engineering, Master's programme
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Basic Linear Algebra: bases, scalar product, least squares problem, eigenvalue problems. Basic signal processing (corresponding to Linear Systems): sampling, convolution and Fourier transform of one-variable signals. Basic skills in Matlab is recommended.Intended learning outcomes
The aim of the course is to give profound knowledge of how different medical images, volumes and sequences are generated and analyzed. Focus is especially on techniques and methods related to magnetic resonance tomography (MRT). A central part of the course is devoted to the design of multi dimensional filters and algorithms for the purpose of extracting different types of information from the medical data sets. After the course the student will be able to:
- Be able to optimize multi dimensional filters with respect to both frequency and spatial requirements.
- Compute local structure descriptors (Tensors) from image data.
- Use the local structure description to perform adaptive image enhancement.
- Describe image segmentation methods as: watershed, levelsets, and region growing. Implement a segmentation algorithm using active contours.
- Describe transformations and similarity measures for registration/fusion of images. Be able to implement a simple registration.
- Explain the behavior of multi-dimensional signals in the Fourier domain.
- In detail tell how the MRI data are sampled in k-space, and how to avoid related sampling problems.
Course content
Medical imaging systems: Physical principles and image reconstruction algorithms for magnetic resonance tomography (MRI), ultrasound and computer tomography (CT). Analysis methods: Multidimensional Fourier analysis, local structure analysis in 2D, 3D and 4D (3D + time), motion/velocity estimation, registration, segmentation using adaptive contours and surfaces. Applications: Image enhancement, image registration, functional magnetic resonance imaging (fMRI).
Teaching and working methods
The course consists of lectures, laboratory exercises and a mini project. Lab exercises and the mini project are done in groups of 2 students. Lab exercises are presented orally at scheduled seminars. The mini project consists of 3 scheduled lab sessions and is presented in a written report. To pass the laboratory work you have to show the working code for the lab instructor, participate
in the lab seminars and present the written mini project report.
Examination
| LAB1 | Laboratory Work | 2 credits | U, G |
| TEN2 | Written Examination | 4 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Other information
Supplementary courses: Multidimensional Signal Analysis, Computer Vision, Medical Imaging , Neural Networks and Learning Systems
Department
Institutionen för medicinsk teknikDirector of Studies or equivalent
Linda RattfältExaminer
Hans KnutssonCourse website and other links
Education components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Course literature
Kompendium om MR, registrering och segmentering. A. Eklund, M. Andersson och H. Knutsson. IMT 2010. Utdelat material| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory Work | 2 credits | U, G |
| TEN2 | Written Examination | 4 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
Kompendium om MR, registrering och segmentering. A. Eklund, M. Andersson och H. Knutsson. IMT 2010.
Utdelat material
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
|
X
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TEN2
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
|
X
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TEN2
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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TEN2
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| 2.2 Experimentation, investigation, and knowledge discovery |
|
X
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LAB1
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| 2.3 System thinking |
X
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X
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TEN2
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| 2.4 Attitudes, thought, and learning |
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X
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LAB1
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
|
X
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LAB1
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| 3.2 Communications |
|
X
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LAB1
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| 3.3 Communication in foreign languages |
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X
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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X
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LAB1
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| 4.4 Designing |
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X
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LAB1
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| 4.5 Implementing |
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X
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LAB1
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| 4.6 Operating |
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X
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LAB1
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
|
X
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LAB1
|
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