Universität Wien FIND

300154 UE 3D Image data: processing, landmarking and template building (2021S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 15 participants
Language: English


Classes (iCal) - next class is marked with N

Dates and times will be decided with the participants during the Vorbesprechung

20 April: 8:00-11:00

21 April: 9:00-12:00

23 April: 14:00-17:00

24 April: 11:00-14:00

27 April: 8:00-11:00

28 April: 9:00-12:00

30 April: 14:00-17:00

04 May: 08:00-11:00

The venue will be the computer room of the micro-CT lab (already reserved) if access to the University premises will be possible. Otherwise it will be conducted online, using Skype or equivalent means.

Monday 15.03. 13:00 - 14:00 Digital (Kickoff Class)
Monday 10.05. 13:30 - 15:00 Digital
Monday 10.05. 17:00 - 18:30 Digital
Tuesday 11.05. 16:30 - 17:30 Digital
Tuesday 11.05. 20:00 - 22:00 Digital
Wednesday 12.05. 16:30 - 19:30 Digital
Friday 14.05. 12:00 - 15:00 Digital
Monday 17.05. 13:30 - 15:00 Digital
Monday 17.05. 17:00 - 18:30 Digital
Tuesday 18.05. 16:30 - 17:30 Digital
Tuesday 18.05. 20:00 - 22:00 Digital
Wednesday 19.05. 16:30 - 19:30 Digital
Friday 21.05. 12:00 - 15:00 Digital


Aims, contents and method of the course

The main aim of the course is applying virtual tools and techniques in order to build a template dataset suitable for the investigation of a given biological object in order to address hypothetical biological question(s). The participants will be offered diverse didactical data sets from which to choose. The template for the analysis of the biological object(s) chosen will be built using coordinate variables (i.e., landmarks, curve semilandmarks, surface semilandmarks, pseudolandmarks, outlines). Other variables, such as surface area or volume can be considered too. Literature pertinent to the biological object selected will be provided for facilitating the formulation of possible biological questions. Further reading will be up to the participant.
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.)

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.

Minimum requirements and assessment criteria

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.

Examination topics

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.

Reading list

Association in the course directory


Last modified: We 15.03.2023 00:24