Student Offers

When segmenting and visualizing intracranial aneurysms in three-dimensional (3D) angiograms, there is often a tendency to overemphasize the neck of the aneurysm, whereas its nature plays a crucial role in the morphological analysis for selecting the appropriate interventional procedure. Using two-dimensional (2D) angiographic imaging, the true morphology can be more accurately assessed if the projection direction is appropriate. On the one hand, such 2D data are obtained in the form of additional high-resolution images during diagnosis or intervention. On the other hand, they are available in the form of lower resolution 2D raw data from the acquisition of the 3D images themselves.

In this thesis, both types of 2D images will be tested for their suitability to be used as an automated mask for the optimization of 3D visualization and segmentation in order to improve the morphological quality of 3D visualization and segmentation.

The implementation will be done in Python using the open source tools Visualization Toolkit (VTK – https://vtk.org) for segmentation and visualization and if necessary Insight Toolkit (ITK – https://itk.org) or SimpleITK (https://simpleitk.org) for any necessary registration between 2D and 3D image series.

Type: Bachelor/ or Master Thesis

Requirements: Good skills in scientific reading; critical thinking; good skills in programming (Python, VTK and related toolkits) 

The comprehensible communication of medical research to the broad public plays an important role in many situations, such as education about preventive examinations or vaccinations. Recently, narrative visualization, i.e. the combination of storytelling techniques with interactive graphics is used to communicate scientific findings. A variety of information visualizations such as diagrams and 2D maps have been used to visually communicate scientific findings. However, little research has been done on how comprehensible annotated diagrams such as bubble charts or medical expert diagrams such as Kaplan-Meier plots are for the broad public or how these representations need to be adapted.

Goal: The goal should be to investigate different information visualization techniques regarding their suitability to visually communicate medical information to the broad public. Based on this analysis, guidelines should be derived on how information visualizations need to be adapted to become understandable for people without specific medical background knowledge. The adapted visualizations should be evaluated with participants from the broad public to validate their understandability.

Type: Bachelor/ or Master Thesis (Team project (2 FIN students) would also be possible)

Requirements: Good skills in scientific reading; critical thinking; good skills in graphics programming (exact languages like D3 or OpenGL can be chosen freely) 

References
[1] Morris, T., et al. “Proposals on Kaplan–Meier plots in medical research and a survey of stakeholder views: KMunicate.” BMJ open 9.9 (2019): e030215.: https://bmjopen.bmj.com/content/9/9/e030215.abstract
[2] Drucker, S., et al. “Communicating data to an audience.” In Data-driven storytelling, pp. 211-31. AK Peters/CRC Press, 2018: chrome-extension://oemmndcbldboiebfnladdacbdfmadadm/https://hal.archives-ouvertes.fr/hal-02310515/document
[3] Meuschke, M., et al. “Towards Narrative Medical Visualization.” arXiv preprint arXiv:2108.05462 (2021).: https://arxiv.org/abs/2108.05462

Within the European A-CINCH project, which addresses the loss of the young generation’s interest for nuclear knowledge, virtual experiments are developed.

Tasks:

• Develop a radiochemistry experiement as a VR and web application
• Evaluate its user experience and usability

The project has to be realised in the game engine Unity, thus the following is required:

• Knowledge of basic computer graphics
• Experience with C# and Unity

We offer:

• interesting clinically relevant research
• support in technical questions and writing of the thesis

We expect:

• good programming skills (Python)
• knowledge of image processing
• experience with Deep Learning and frameworks (Pytorch, Tensorflow, Keras)
• good study achievements

In cerebral aneurysm research, CFD simulations allow us to gain a better understanding of the dynamics of the blood flow. The simulated flow is often visualized using integral curves resulting in cluttered “spaghetti plots”. Advanced approaches group similar curves and show only selected representatives (image). These approaches however, fail in showing the clusters’ spatial extent. In this thesis, an interactive approach facilitating a continuous transition between the full set of integral curves and an uncluttered abstracted visualization shall be developed. Browsing back and forth through various levels of abstraction shall allow the user to grasp both, the general structure of the blood flow pattern as well as the spatial extent of individual substructures.

Requirements: Good to very good programming skills (C++) are mandatory

Im Rahmen der Arbeit sollen Stereoverfahren für die 3D-Rekonstruktion von Strukturen aus intraoperativen Endoskopiebildern entwickelt werden. Die Arbeit wird in enger Kooperation zwischen der Fakultät Informatik der OvGU Magdeburg (Dr. Sandy Engelhardt) und der Herzchirurgie des Universitätsklinikums Heidelberg (Prof. De Simone) durchgeführt. Weitere Themen für Abschlussarbeiten sind vorhanden. Melden Sie sich gern bei Interesse.

Aufgaben

• Meshing einer rekonstruierten 3D-Punktewolke
• Texturierung der Oberfläche
• Fusion von verschiedenen Ansichten zu einem Mesh

Anforderungen: Programmiererfahrung in C++ (OpenCV- Kenntnisse hilfreich)