This course covers a selection of the most used image analysis methods, with emphasis on images from medical and biological modalities, from microscopy, to ultrasound, MRI, or CT, including time sequences. We describe some of the most used algorithms for solving the key problems in this area - preprocessing, segmentation, registration, reconstruction and classification - and their use in applications. We show how to deal with the specifics of medical data such as non-linear transformation, 3D data, large variability, lack of reliable keypoints, lack of labeled training data etc. This course complements the Computer Vision Methods course, which covers techniques for images from standard optical cameras.
This course assumes the knowledge of basic image processing algorithms, as taught for example in the Digital image course. We assume the knowledge of programming, mathematics and machine learning approximately at the level of the bachelor programs here at FEE (FEL). The knowledge of medical image acquisition devices principles (taught for example in the course BEAM33ZSL) is useful but not necessary.
Lecturer: Jan Kybic (kybic@fel.cvut.cz), consultations by appointment.
Lab assistant: Denis Baručić (barucden@fel.cvut.cz), consultations by appointment.
In the lectures, we will present a number of relevant algorithms for (bio)medical image processing based on the original scientific papers. You are strongly advised to read the papers in advance. Feel free to ask questions, both in advance and during the lecture. The selection of papers can be adapted to some extent, so if there is a particular topic that you are interested in or not interested in at all, let us know.
The Labs will take place in a computer laboratory. In the first part of the semester, you will try to implement some simple algorithms, using available libraries for the more complicated methods. During the second part of the semester, you will work on your Semester work.
The Semester work should take you about 10h. It will consist in an independent implementation of some biomedical image analysis algorithm or its application to a particular problem. You are free to choose your own topic, please approach us if you have an idea. Otherwise, you will be assigned a topic. You are expected to submit a short report (5-10 pages including images) and your code. You should also present your results briefly (5 minutes + equations) to your peers. The presentation can be short but it should explain what the problem was, how others solved it, how you solved it and how well it worked. The presentation should be understandable for your peers. The report should be structured similarly but with more details, equations, images and graphs. The code should be commented. This is required to pass the course (get zápočet).
The exam will be oral and in person (epidemiological situation permitting) and the student should demonstrate the knowledge of the basic principles of the discussed algorithms. The results will be determined by from the evaluation of the semester work (50%), oral exam (40%) and activity during the labs and lectures (10%). None of the three parts should be evaluated as F (fail).
The exam will take place on Wednesdays, January 18, January 25 and February 1 in room KN:G-104 between 9:15 and approximately 10:45 . Please contact the lecturer to agree on a specific time. You need to sign in for the exam to KOS, too.