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The human entorhinal region consists of a number of areas; however, there is no generally accepted nomenclature for these cytoarchitectonic fields, and the designation of its constituent layers or strata is a matter of controversy. Here, we consider a hitherto neglected adjacent field, the preamygdaloid claustrocortex. Its medial subfield has a small common(More)
We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for automated tumor segmentation. The practicality of current learning-based automated tissue classification approaches is severely impeded by their dependency on manually segmented(More)
BACKGROUND AND PURPOSE The anterior communicating artery (ACoA) is a site of predilection for intracranial saccular aneurysms causing subarachnoid hemorrhage. ACoA aneurysms are frequently associated with an asymmetrical circle of Willis. In such cases, the ACoA is probably exposed to high hemodynamic stress caused by a considerable shunt flow across the(More)
Purpose To evaluate whether radiomic feature-based magnetic resonance (MR) imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma with improved accuracy compared with that of established clinical and radiologic risk models. Materials and Methods Retrospective evaluation of data was approved by the(More)
Current developments in the health care sector are marked by the increased digitalisation of patient records, the use of electronic devices as supporting tools in patient care, and the employment of sensors (e.g. monitoring devices and surgery recording devices), which contribute directly to the abundance of medical data. However, before any significant(More)
Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached(More)
Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucial. Recent developments in the area of cognitive computing(More)