Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.
300154 UE 3D Image data: processing, landmarking and template building (2021S)
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 11.02.2021 08:00 bis Do 25.02.2021 18:00
- Abmeldung bis Mi 31.03.2021 18:00
Details
max. 15 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Dates and times will be decided with the participants during the Vorbesprechung
Veranstaltungsort ist der Computerraum des Mikro-CT-Labors (bereits reserviert), sofern der Zugang zu den Räumlichkeiten der Universität möglich ist. Andernfalls wird es online, mit Skype oder gleichwertigen Mitteln durchgeführt.- Montag 15.03. 13:00 - 14:00 Digital (Vorbesprechung)
- Montag 10.05. 13:30 - 15:00 Digital
- Montag 10.05. 17:00 - 18:30 Digital
- Dienstag 11.05. 16:30 - 17:30 Digital
- Dienstag 11.05. 20:00 - 22:00 Digital
- Mittwoch 12.05. 16:30 - 19:30 Digital
- Freitag 14.05. 12:00 - 15:00 Digital
- Montag 17.05. 13:30 - 15:00 Digital
- Montag 17.05. 17:00 - 18:30 Digital
- Dienstag 18.05. 16:30 - 17:30 Digital
- Dienstag 18.05. 20:00 - 22:00 Digital
- Mittwoch 19.05. 16:30 - 19:30 Digital
- Freitag 21.05. 12:00 - 15:00 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Attendance: attendance of the course is compulsory. Absences are allowed up to 80% of the total number of hours. During the course, the participants will be practicing tools and techniques useful for image manipulation and specifically suited for the data set they have selected. Discussion on the possible hypothetical biological questions to address will be constantly held in the class.
Homework exercises: participants are asked to complete works left unfinished during the class time and are invited to practice in the computer room after the class hours
Test: At the end of the course participants must present the outcome of their work to the teacher and the rest of the class (see section Prüfungsstoff - Englisch). One lesson (usually the one preceding the date of the exam) will be specifically devoted to practice tools and procedures necessary to successfully pass the exam.
Homework exercises: participants are asked to complete works left unfinished during the class time and are invited to practice in the computer room after the class hours
Test: At the end of the course participants must present the outcome of their work to the teacher and the rest of the class (see section Prüfungsstoff - Englisch). One lesson (usually the one preceding the date of the exam) will be specifically devoted to practice tools and procedures necessary to successfully pass the exam.
Mindestanforderungen und Beurteilungsmaßstab
In order to attend the course, the participants are required to have passed the basic course 300038-1 UE Virtual images manipulation and segmentation. Alternatively, they should have independently acquired basic skills in 3D virtual image manipulation.
Prüfungsstoff
Through the course and with the constant support of the teacher, the participant will be asked to work on a given 3D image data set, built a template data set (with the aim to address hypothetical biological questions). The outcome of this work must be orally presented to the teacher and the rest of the class using a slide presentation. The focus of the presentation is mainly on the methodological aspects. However, no statistical analysis is requested since that is not the purpose of the course (moreover, the participants will mostly work on a sample composed of one single specimen). The files produced (presentation file and networks) should be handed in for evaluation. The performance of the student will be evaluated mostly based on the technical skills applied for the development of the project. Clarity and completeness of the presentation will be considered as an additional merit. The exam is based on the content of the course and on topics thoroughly discussed in class.
Literatur
Zuordnung im Vorlesungsverzeichnis
MAN W5, MAN 3
Letzte Änderung: Fr 12.05.2023 00:23
Additionally, Amira software advanced tools (e.g., superimposition of datasets, advanced image segmentation) will be illustrated.
Amira and EvanToolbox will be available to the participants and will be mainly used.
(Participants are asked to have a capable hard disk to work on.)