Jurgen Wallner's scientific contributions

Citations

... While many of the aforementioned works rely on a manual alignment of virtual content with the patient, several publications within this category focus on addressing these technical challenges. Mostly, they do not focus on specific medical applications, but develop new concepts for system calibration [6,82,57] or image-to-patient-registration [217,35,156,201,77], which could be applied in various medical scenarios. Other works evaluate and compare selected technical aspects [58,138,205,79,157]. ...
... Medical imaging deals with the acquisition of human and animal images from cellular to body scale. Common examples include computed tomography (CT) and magnetic resonance imaging (MRI), which allow to acquire images at vascular and organ level for diagnostic and therapeutic reasons Gsaxner et al., 2019a;Gsaxner et al., 2018). In this context, Lundervold & Lundervold (2019) provide an analysis of deep learning-based methods in medical imaging with a focus on MRI acquisitions. ...