PV187 Seminar of digital image processing

Faculty of Informatics
Autumn 2022
Extent and Intensity
0/0/2. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Martin Maška, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Tue 12:00–13:50 A321
Prerequisites
SOUHLAS
Knowledge at the level of the course PV131 Digital Image Processing and PB130 Introduction to Digital Image Processing is required as well as practical experience with digital image processing (e.g., gained in course PV162 Image Processing Project).
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 70 fields of study the course is directly associated with, display
Course objectives
The student will gain a more profound knowledge about a chosen area of image processing solved in the Centre for Biomedical Image Analysis at FI MU and will study literature on a selected practical topic followed by a presentation in English. This will strengthen the student's capability of understanding real-world problems in the given field, finding suitable solutions and participating in scientific team discussions.
Learning outcomes
The student will be able to:
describe and share own image analysis solutions with colleagues;
prepare an oral presentation about specific image analysis workflow;
analyze strengths and weaknesses of image analysis workflows presented by others;
suggest suitable modifications to image analysis workflows presented by others;
Syllabus
  • This course is a seminar (presentations followed by team discussions) focused on methods of acquisition and processing of digital images of cells, tissues and organs, especially in connection with biomedical research held in the Centre for Biomedical Image Analysis at FI MU.
Literature
  • Scientific books and articles according to the recommendation of project supervisor.
Teaching methods
The core work consists in studying a research problem from literature or online resources including the behaviour of selected methods according to the supervisor's instructions. Active participation in the research seminar is expected including own presentation in English once per semester.
Assessment methods
Communication with project supervisor in Czech or English, study materials in English. Individual work with literature and online resources, a final presentation on the seminar in English (notebook and data projector available).
Language of instruction
English
Further Comments
The course is taught each semester.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2022, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2022/PV187