Bjoern MenzeOpen OpportunitiesIn this master's thesis project, we are looking for a candidate to apply machine learning techniques to correct and predict signals of incomplete CT perfusion imaging for ischemic stroke. We hope to use machine learning techniques to de-noise and correct for the truncation in CT perfusion signals. In particular, we aim to infer the true attenuation curve after the truncation time-point. - Artificial Intelligence and Signal and Image Processing, Central Nervous System, Radiology and Organ Imaging
- Master Thesis
| This is a clinical image registration and visualization project that tries to map a zoomed-in CT view with a zoomed-out MR modality. The CT view can see very detailed blood vessels and bones, while the MR view sees the soft brain tissues but without vessels. The clinicians want to register them together automatically, as they are currently aligning the two views by hand manually and takes them a lot of time. The outcome of this project is an automated, fast, and accurate image co-registration software that can be deployed in the hospital to improve clinical care. - Information, Computing and Communication Sciences, Medical and Health Sciences
- Internship, Master Thesis, Semester Project
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