Robust and accurate cerebral hemisphere segmentation in non-contrast CT using a 2.5D Dense U-Net
| dc.contributor.advisor | Kachergis, G.E. | |
| dc.contributor.author | Kleef, van, J.A. | |
| dc.date.issued | 2018-06-28 | |
| dc.description.abstract | This work is about automatically segmenting cerebral hemispheres using a convolutional neural network. The aim is to publish the work in NeuroImage: Clinical, since it is the rst work to automatically segment cerebral hemisphere in non-contrast CT scans. Some sections can lack background information, for the sake of conciseness of being it a paper for a targeted journal. The background information that is relevant can be found in the included appendices. Also more work that is done in the framework of the extended research project is included in the appendices For the last eight months I worked on this extended research project at the Radboud Hospital Nijmegen in the Digital Image Analysis group (DIAG). Besides the fact that I learned much in this period, be it academical, medical or technical, I had a very good time here. I would like to thank this group for the excellent guidance, especially Ajay and Rashindra, who supervised me through the entire process. I would also like to thank George for supervising on behalf of the university. | en_US |
| dc.embargo.lift | 10000-01-01 | |
| dc.embargo.type | Permanent embargo | en_US |
| dc.identifier.uri | https://theses.ubn.ru.nl/handle/123456789/7083 | |
| dc.language.iso | en | en_US |
| dc.thesis.faculty | Faculteit der Sociale Wetenschappen | en_US |
| dc.thesis.specialisation | Master Artificial Intelligence | en_US |
| dc.thesis.studyprogramme | Artificial Intelligence | en_US |
| dc.thesis.type | Master | en_US |
| dc.title | Robust and accurate cerebral hemisphere segmentation in non-contrast CT using a 2.5D Dense U-Net | en_US |
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