Abstract
Decision-making in acute ischemic stroke is complex. Imaging characteristics of the ischemic brain and the neurovasculature provide critical information for therapeutic decisions as they have shown to be associated with treatment-related risks and benefits and patient outcome. However, to be useful in daily clinical practice, imaging parameters must be measured rapidly and in a reproducible manner. The aim of this thesis was to introduce and evaluate automated image processing methods to accurately assess radiological images of acute stroke patients, with the ultimate goal to improve decision-making in acute ischemic stroke.
| Original language | English |
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| Qualification | Doctor of Philosophy |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 6 Apr 2018 |
| Place of Publication | Enschede |
| Publisher | |
| Print ISBNs | 9789036545112 |
| Publication status | Published - 6 Apr 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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