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3d Morphometrics and Image Analysis with Slicermorph
Provider: Faculty of Science

Activity no.: 5935-26-00-00	There are 26 available seats
	Enrollment deadline: 15/05/2026

Place	Department of Plant and Environmental Sciences
Date and time	06.07.2026, at: 09:00 - 10.07.2026, at: 16:00
Regular seats	30
Lecturers	Staffan Persson Christy Anna Hipsley
ECTS credits	2.50

Contact person	Staffan Persson E-mail address: staffan.persson@plen.ku.dk

Enrolment Handling/Course Organiser	PhD Administration SCIENCE E-mail address: phdcourses@science.ku.dk

Enrolment guidelines This is a toolbox course where 80% of the seats are reserved for PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% of the seats are reserved for PhD students from other Danish Universities/faculties (except CBS). Seats will be allocated on a first-come, first-served basis and according to the applicable rules. Anyone can apply for the course, but if you are not a PhD student at a Danish university (except CBS), you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to applicants on the waiting list. *Special rules apply for this course* All applicants must register for the course and also sent a motivational email to either Staffan.persson@plen.ku.dk, or to christy.hipsley@snm.ku.dk Aim and Content Aims: The course is a combination of formal didactics and computer labs that accompany the content. Lecturers will cover topics in theory of statistical shape analysis, applied imaging, and related topics. Labs will cover all aspects of conducting specimen-based, morphology research using 3D imaging. Practical topics (e.g., image processing and segmentation, visualization) will be taught using the open-source 3D Slicer visualization suite and the SlicerMorph morphometrics toolkit (statistical shape analysis). Additional lab topics include using 3D specimen repositories to obtain data, tools and methods for collaboration and reproducible research (git and github), how to bridge 3D Slicer with R statistical environment for domain specific inferential analysis. Course material will focus on volumetric (e.g., CT or microCT) 3D datasets, but will be equally applicable to data from 3D surface scanners. Course content over 5 days consists of morning lectures followed by afternoon hands-on practical exercises and opportunities for one-on-one training. The final day will end with student presentations. Learning outcomes Intended learning outcome for the students who complete the course: Knowledge: • Distinguish between data types used in shape analysis • Understand landmark-based Procrustes paradigm underlying geometric morphometrics Skills: • Collect digital shape data from online sources • Place landmarks on 3D models • Perform Procrustes Superimposition • Visualise shape differences using PCA • Perform shape statistics in R environment Competences: • Use 3D Slicer software and various modules • Produce statistical models for analysing and comparing shapes Target Group The course is aimed at senior undergraduates, graduate students, post-docs and junior faculty who are interested in conducting quantitative morphological research using 3D imaging data from biological systems. It is also appropriate for more established researchers who are looking for open-source alternatives to the proprietary tools they have been using. Recommended Academic Qualifications Enrolled in or completed studies in Natural or Computer Sciences. Students are expected to come with a project, ideally with sample data of their own to work on throughout the course. Each attendee should bring a recent (last two years) laptop running Windows, Mac or Linux OSes (no netbooks or tablets). Research Area 3D image data such as CT, MRI and synchrotron are increasingly incorporated into biological research, as well as biomedical studies. While obtaining and working with such data has been historically limited to medical labs with large computational resources, recent advances in open-source software is democratizing this process. The software 3D Slicer is now a leader in this field, with a growing toolkit of extensions, modules and custom software distributions tailored to the needs of diverse research communities. Teaching and Learning Methods The course is organized in morning theoretical and afternoon practical sessions. Course format will be highly collaborative, and labs will be done in small teams. Prior experience with tools is not expected, but will positively impact the learning experience. Type of Assessment Short (10 minute) student presentations on the last day, showing some aspect of 3D image analysis covered in the course. Literature The open-source 3D Slicer visualization suite and the SlicerMorph morphometrics toolkit (statistical shape analysis) https://www.slicer.org/ Rolfe et al. 2021. SlicerMorph: An open and extensible platform to retrieve, visualize and analyse 3D morphology. Methods Ecol Evol. 2021;12:1816–1825. Course coordinator Professor Staffan Persson, Associate Professor Christy Hipsley Guest Lecturers Course lecturer: Associate Professor Murat Maga Dates 6th to 10th July, 2026 Course location TBA Registration deadline 15 May 2026 Course fee • Participant fee: DKK 0 • PhD student enrolled at SCIENCE: DKK 0 • PhD student from Danish PhD school Open market: DKK 0 • PhD student from Danish PhD school not Open market: DKK 3.000 • PhD student from foreign university: DKK 3.000 • Master's student from Danish university: DKK 0 • Master's student from foreign university: DKK 3.000 • Non-PhD student employed at a university (e.g., postdocs): DKK 3.000 • Non-PhD student not employed at a university (e.g., from a private company): DKK 8.400 Cancellation policy • Cancellations made up to two weeks before the course starts are free of charge. • Cancellations made less than two weeks before the course starts will be charged a fee of DKK 3.000 • Participants with less than 80% attendance cannot pass the course and will be charged a fee of DKK 5.000 • No-show will result in a fee of DKK 5.000 • Participants who fail to hand in any mandatory exams or assignments cannot pass the course and will be charged a fee of DKK 5.000 Course fee and participant fee PhD courses offered at the Faculty of SCIENCE have course fees corresponding to different participant types. In addition to the course fee, there might also be a participant fee. If the course has a participant fee, this will apply to all participants regardless of participant type - and in addition to the course fee.

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