J Imaging
December 2024
In recent years, synthetic Computed Tomography (CT) images generated from Magnetic Resonance (MR) or Cone Beam Computed Tomography (CBCT) acquisitions have been shown to be comparable to real CT images in terms of dose computation for radiotherapy simulation. However, until now, there has been no independent strategy to assess the quality of each synthetic image in the absence of ground truth. In this work, we propose a Deep Learning (DL)-based framework to predict the accuracy of synthetic CT in terms of Mean Absolute Error (MAE) without the need for a ground truth (GT).
View Article and Find Full Text PDFObjective: This retrospective multicenter study aimed to evaluate surgical versus conservative treatment in patients with hypopharyngeal and laryngeal cancer under real world conditions.
Methods: This study included 2307 patients diagnosed with hypopharyngeal or laryngeal squamous cell carcinoma (SCC) in five German tertiary head and neck centers between 01/2004 and 12/2014. Overall, 783 patients with advanced SCC consecutively underwent laryng(opharyng)ectomy (L(P)E).
Objectives: Virtual reality (VR) appears to be a promising educational tool for otorhinolaryngology (ORL) residency training, as it allows for safe and effective practice immediate feedback and potential improvements in patient outcomes. Despite these advantages, VR has not yet been incorporated into residency training in ORL, which may be due to limited availability or validation and skepticism toward incorporation of new training methods. This study investigates whether a VR model of the temporal bone improves learning success for ORL residents in comparison to standard plastic models and whether it depends on surgeon's experience.
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