CM201V Medial Image Registration 3.0 credits

• Overview of image registration
• Linear registration
• Non-linear registration
• Registration with a priori information

The course consists of lectures, laboratories, mathematical exercises, and an exam. Participants combine basic and advanced software libraries for image registration in Python, including scipy, numpy, SimpleITK, scikit-image, etc. The course also includes introductory labs for students with programming experience but no Python experience.

Image registration is used to align images from the same or different modalities to each other. Image registration is important for the diagnosis and treatment of various diseases. The course covers concepts, theories, and the most used methods in image registration. The course is focused on solving medically relevant problems.

After completing the course, the participant should be able to:

• Understand the key issues and challenges in image registration
• Describe the main principles and methods and the main differences between them
• Summarize the advantages and disadvantages and scope of different methods
• Identify and understand the mathematical theory behind the most used methods
• Develop and systematically evaluate different methods for solving simplified problems
• Analyze the effect of different parameters of methods in particular situations
• Explain the proposed strategy for solving specific problems

in order to:

• understand the complete workflow for using computational tools for image registration in a medical context
• be able to implement computational solutions in image registration to medically relevant problems
• have a broad knowledge base that can facilitate understanding literature in the field

Bachelor's degree in Medical Technology, Engineering Physics, Electrical Engineering, Computer Science or equivalent. At least 6 credits in programming. English B/English 6.

If the course is discontinued, students may request to be examined during the following two academic years.

• LAB1 - Laborations and exercises, 1.5 credits, grading scale: P, F
• TEN1 - Written exam, 1.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Rodrigo Moreno

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

The target group for this course are persons who are not program students at KTH.