Labs

The labs cover selected image processing methods. For each method, the students are provided with a Jupyter notebook that contains a brief explanation and a template for the implementation. The students are tasked to follow the template and complete the implementation.

Attendance at the labs is recommended but not mandatory. However, if you do not attend, you will not get points for the quizzes.

See information about the semester work.

Schedule

Week	Date	Topic	Quiz topics
1	27. 9.	Introduction	no quiz
2	4. 10.	Active contours	1.1, 1.3
3	11. 10.	Point distribution models	2.1, 2.2
4	18. 10.	SLIC	3.1, 3.3
5	25. 10.	Texture features & Graphcut	4.1, 4.2
6	1. 11.	Deep learning: segmentation (U-Net)	5.1, 5.2
7	8. 11.	Cell detection	6.1, 6.2
8	15. 11.	Frangi vesselness filter	no quiz
9	22. 11.	Nodule detection (data)	8.1, 8.2
10	29. 11.	B-splines	9.1, 9.2
11	6. 12.	Registration	10.1, 10.2
12	13. 12.	Registration (Simple ITK)	11.1, 11.2 + B-splines from lecture
13	20. 12.	Semester work: consultation	no quiz
14	10. 1.	Semester work: presentation	no quiz

Required software

Although the students can use the lab computers, they are encouraged to use their own devices, which will allow them to work on the assignments at home. The easiest way to install all required software is through the Conda system. Use the Miniconda installer to obtain a Conda installation.

After installing Conda, create a new environment and install the required dependencies:

conda create -n zmo python=3 jupyter matplotlib numpy

To verify the installation, activate the fresh environment

conda activate zmo

and check that the following commands exit successfuly:

python -c "import numpy; import matplotlib"
jupyter notebook --version

It is necessary to activate the Conda environment before using Jupyter, so it is required to run

conda activate zmo

before working on the assignments.

Table of Contents

Labs

Schedule

Required software