Nils Jacobson defended his Master thesis on 16 February 2021. Congrats!

Nils Jacobson defended his Master thesis in MPCAS at the Chalmers University of Technology on 16 February 2021. Congrats!

Screenshot of Nils Jacobson’s Master Thesis defence.
Title: Vascular Bifurcation Detection in Cerebral CT Angiography Using CNN and Frangi Filters

Segmentation and feature extraction are important tools for analysing and visualizing information in medical image data, particularly in vascular image data which relates to widely spread vascular diseases. Vessel segmentation is extensively featured in research, recently adapting trends in deep learning image processing. This paper aims to develop a vessel bifurcation detection method to support a seed point based segmentation approach. The suggested approach is a combination of classification, with a convolutional neural network (DenseNet), local vessel segmentation, with Frangi filters, and 3D morphological skeletonization. A small data set is produced for network training and evaluation. Results indicate a high classification accuracy which filters problematic samples for the Frangi filter. Thus the combination is able to suggest quality branch seed points under most circumstances. Next step would be to expand the data set to enable further optimization and more rigid evaluation. In any case a combination of a high performance classifier followed by qualitative assessment of local samples show potential.​

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Jonna Hellström and Giovanni Volpe
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Eva Škvor

Place: Online via Zoom
Time: 16 February, 2021, 16:00

Link: Master thesis presentation Nils Jacobson

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