Cooperative AI training for cardiothoracic segmentation in computed tomography: An iterative multi-center annotation approach.

Purpose: Radiological reporting is transitioning to quantitative analysis, requiring large-scale multi-center validation of biomarkers. A major prerequisite and bottleneck for this task is the voxelwise annotation of image data, which is time-consuming for large cohorts. In this study, we propose an iterative training workflow to support and facilitate such segmentation tasks, specifically for high-resolution thoracic CT data.

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach.

Objectives: To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.

Methods: CTA exams of the aorta of 191 patients (68.1 ± 14 years, 128 male), performed between 2015 and 2018, were retrospectively identified from our imaging archive and manually segmented by two investigators.

Remifentanil-induced tolerance, withdrawal or hyperalgesia in infants: a randomized controlled trial. RAPIP trial: remifentanil-based analgesia and sedation of paediatric intensive care patients.

Background: Short-acting opioids like remifentanil are suspected of an increased risk for tolerance, withdrawal and opioid-induced hyperalgesia (OIH). These potential adverse effects have never been investigated in neonates.

Objectives: To compare remifentanil and fentanyl concerning the incidence of tolerance, withdrawal and OIH.

New vessel analysis tool for morphometric quantification and visualization of vessels in CT and MR imaging data sets.

Image processing algorithms and a prototypical research software tool have been developed for visualization and quantitative analysis of vessels in data sets from computed tomography and magnetic resonance imaging. The software is based on a sequence of processing steps, which are as follows: (a) vessel segmentation based on a region growing algorithm, (b) interactive "premasking" to optionally exclude interfering structures close to the vessels of interest, (c) distance transform-based skeletonization, (d) multiplanar reformation orthogonal to the vessel path, (e) identification of the lumen boundary on the orthogonal cross-section images, and (f) morphometric measurements. The development of the algorithmic components and the application user interface has been carried out in close cooperation with clinical users to achieve a high degree of usability and flexible support of work flow.