PV187 Laboratory of Optical Microscopy

Faculty of Informatics
Autumn 2009
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. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Timetable
Thu 14:00–15:50 C525
Prerequisites
SOUHLAS
Knowledge at the level of the course PV131 Digital Image Processing is required.
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
Course objectives
The student will gain a deeper knowledge about a chosen area of optical microscopy image processing solved in the Centre for Biomedical Image Analysis at FI MU and will apply this knowledge during the work on a team R&D project. This will strengthen the student's capability of analyzing real-world problems in the given field, finding suitable solutions and working in a scientific team.
Syllabus
  • This course is a team project aimed at new methods of acquisition and processing of digital images of cells from optical microscopes, 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 solving a research problem including implementation of selected methods according to the supervisor's instructions.
Assessment methods
Communication with project supervisor in Czech or English, study materials in English. Individual work on computer, short final presentation on seminar (notebook and data projector available).
Language of instruction
Czech
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, 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, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2009, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2009/PV187