Syllabus for Digital Imaging Systems

Digitala bildalstrande system

  • 7.5 credits
  • Course code: 1MD130
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F, Computer Science A1F

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2020-02-27
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2022-10-24
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2023
  • Entry requirements:

    120 credits including participation in either Introduction to Image Analysis or Computer-Assisted Image Analysis. Proficiency in English equivalent to the Swedish upper secondary course English 6.

  • Responsible department: Department of Information Technology

Learning outcomes

On completion of the course, the student should be able to:

  • describe the physics and technique behind modern imaging techniques
  • describe basic principles for sample preparation in relation to the different imaging techniques
  • reason and analyse around the possibilities and limitations in resolution with regards to time, space and spectrum
  • describe how the different techniques affect the imaged sample, and reason about the effects that might have on the image and subsequent interpretation/analysis
  • judge and reason about the suitability of different imaging techniques in combination with image processing/analysis and machine learning methods for different applications

Content

The course will present different imaging techniques that have been developed over the last decades in a unified way, and to compare and contrast the possibilities and limitations with the respective techniques. Techniques that will be covered in the course are different sensor types, laser scanning, multispectral imaging, microscopy (light, fluorescence, electron), and medical imaging systems (MR, CT, PET, SPECT, US).

Instruction

Lectures by experts in the different imaging techniques.

Assessment

Written exam.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Syllabus Revisions

Reading list

The reading list is missing. For further information, please contact the responsible department.

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