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Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice.In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance.Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p 0.94) for any of the comparison made between the two groups.Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.

The COVID-19 pandemic has become one of the main international concerns regarding its impact on mental health. The present study aims to investigate the prevalence of depression, anxiety, and stress symptoms, and behavioral aspects amidst the COVID-19 pandemic in a Brazilian population. An online survey was administered from May 22 to June 5, 2020 using a questionnaire comprising of sociodemographic information, the Depression, Anxiety, and Stress Scale (DASS-21), and the Coping Strategies Inventory. Participants comprised 3,000 people from Brazil's 26 states and the Federal District, with an average age of 39.8 years, women (83%), married (50.6%), graduates (70.1%) and employees (46.7%). Some contracted the virus (6.4%) and had dead friends or relatives (22.7%). There was more consumption of drugs, tobacco, medication, and food (40.8%). Almost half of participants expressed symptoms of depression (46.4%), anxiety (39.7%), and stress (42.2%). These were higher in women, people without children, students, patients with chronic diseases, and people who had contact with others diagnosed with COVID-19. The existence of a group more vulnerable to situations with a high stress burden requires greater attention regarding mental health during and after the pandemic. That said, it should be emphasized that these findings are preliminary and portray a moment still being faced by many people amid the pandemic and quarantine measures. Therefore, we understand that the magnitude of the impacts on mental health will only be more specific with continuous studies after total relaxation of the quarantine.