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lectures
The following table contains the lecture plan. The Resources column is deliberately extensive, we will most likely not be able to talk about all the methods. Let me know if you have some preferences as to what methods you would like to talk about, I am open to suggestions.
I assume the knowledge of the simple image processing methods such as thresholding or linear filtering. I also assume a basic knowledge of neural networks and deep learning (see links below). However, I can of course briefly explain the basic concepts if you let me know.
The links to download the full text of the papers should work for you, although in some cases you need to be on the CTU network. If they do not work, let me know.
You are supposed to (at least superficially) read the papers before the lecture to get the most of it. There might be a quick test (quiz) at the beginning of the lab session related to some of the papers discussed during the lectures.
Medical image analysis is a dynamic domain, recent and advanced algorithms are published mainly in the primary literature, i.e. scientific journals. The most relevant are
These journals can be accessed free of charge thanks to a CTU subscription. Ask the central library in case of problems.