300121 UE Image analysis and reconstruction of morphological datasets (2024W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 12.09.2024 14:00 bis Do 26.09.2024 18:00
- Abmeldung bis Di 15.10.2024 18:00
Details
max. 10 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
VORBESPRECHUNG: 01.10.24, 15:00 (Zoom, moodle)
- Montag 04.11. 09:45 - 14:45 Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
- Dienstag 05.11. 09:45 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
- Mittwoch 06.11. 09:45 - 16:30 Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
- Donnerstag 07.11. 09:45 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
- Freitag 08.11. 09:45 - 14:45 Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
The course will address image theory, especially what are images and how images can be changed or modified. The acquired skills will particularly focus on image processing and visualization methods of morphological datasets. Open source software such as FIJI (Image J) or drishti will be used during the course. The course does not require any previous knowledge on image processing, but a general interest in the field is expected of the students.Aim of the course is to convey foundations and methods of image theory, image processing and visualization of morphological datasets. After the course, students should independently be able to use image filters, and also conduct quantitative and qualitative analyses of morphological datasets.
Art der Leistungskontrolle und erlaubte Hilfsmittel
Active participation, analysis and understanding of the sample datasets and demonstrations during the course represent one of the main evaluation criteria. Students will receive short projects in groups that will require the acquired skills for analysis (filtering of datasets, volume and surface calculations, segmentation and visualization of datasets). Own projects of e.g. master or phD students are possible. Die achieved result of the short projects will be evaluated in a short oral examination (methods, results, etc.)
Mindestanforderungen und Beurteilungsmaßstab
Presence during course hours is mandatory. Active participation during the trials and experimenting with the provided datasets account for 50% of the grade. A final presentation on the last day plus discussion on the methods applied accounts for the other 50%
Prüfungsstoff
Comprehension of the various programs and image processing and analysis tools. Presentation at the end of the course.
Literatur
Specific references will be provided during the course. Since we only use open source software, various forum of image analysis websites provide the best help.
Zuordnung im Vorlesungsverzeichnis
MBO 7, MZO4, MES5
Letzte Änderung: Mo 23.09.2024 11:47