300154 UE 3D Image data: processing, landmarking and template building (2018S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Fr 09.02.2018 08:00 to Th 22.02.2018 18:00
- Deregistration possible until Sa 31.03.2018 18:00
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 08.03. 11:00 - 12:00 Konferenzzimmer (Kickoff Class)
- Wednesday 25.04. 09:00 - 12:00 EDV-Raum/Selbststudium
- Monday 30.04. 13:00 - 16:00 EDV-Raum/Selbststudium
- Wednesday 02.05. 09:00 - 12:00 EDV-Raum/Selbststudium
- Thursday 03.05. 10:00 - 13:00 EDV-Raum/Selbststudium
- Monday 07.05. 10:00 - 13:00 EDV-Raum/Selbststudium
- Tuesday 08.05. 09:00 - 12:00 EDV-Raum/Selbststudium
- Wednesday 09.05. 10:00 - 13:00 EDV-Raum/Selbststudium
- Friday 11.05. 13:30 - 16:30 EDV-Raum/Selbststudium
Information
Aims, contents and method of the course
Assessment and permitted materials
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.
Minimum requirements and assessment criteria
In order to be suited for 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.
Participants are asked to have a capable hard disk to work on.
Examination topics
Throughout 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.
Reading list
Association in the course directory
MAN W5, MAN 3
Last modified: Sa 22.10.2022 00:29
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.