Bedingt durch die COVID-19-Pandemie können kurzfristige Änderungen bei Lehrveranstaltungen und Prüfungen (z.B. Absage von Vor-Ort-Lehre und Umstellung auf Online-Prüfungen) erforderlich sein. Melden Sie sich für Lehrveranstaltungen/Prüfungen über u:space an, informieren Sie sich über den aktuellen Stand auf u:find und auf der Lernplattform moodle.
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.
Mindestanforderungen und Beurteilungsmaßstab
In order toattend the course, the participants are required to have attended successfully the basic course 300038-1 UE Virtual images manipulation and segmentation. Alternatively, they should have independently acquired basic skills in 3D virtual image manipulation. Participants are asked to have a capable hard disk to work on.
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 must be 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.