Publications by authors named "M Danielsson"

Background: The permitted input power density of rotating anode x-ray sources is limited by the performance of available target materials. The commonly used simplified formulas for the focal spot surface temperature ignore the tube voltage despite its variation in clinical practice. Improved modeling of electron transport and target erosion, as proposed in this work, improves the prediction of x-ray output degradation by target erosion, the absolute x-ray dose output and the quality of diagnostic imaging and orthovolt cancer therapy for a wide range of technique factors.

View Article and Find Full Text PDF

The spatiotemporal resolution of diagnostic X-ray images is limited by the erosion and rupture of conventional stationary and rotating anodes of X-ray tubes from extreme density of input power and thermal cycling of the anode material. Conversely, detector technology has developed rapidly. Finer detector pixels demand improved output from brilliant keV-type X-ray sources with smaller X-ray focal spots than today and would be available to improve the efficacy of medical imaging.

View Article and Find Full Text PDF

The aim of this study was to investigate Swedish children's and parents' attitudes and knowledge about human papillomavirus (HPV) vaccination a year after gender-neutral HPV vaccination was introduced in Sweden's national immunization program (NIP). Additional information about HPV and vaccine was provided in the extended immunazation program. In total, 276 parents and 206 children from 22 School Health Services responded to a web-based survey.

View Article and Find Full Text PDF

The increasing prevalence of threats and violence against ambulance clinicians is a critical issue that has not been adequately studied. These incidents pose significant challenges to the provision of prehospital emergency care, affecting both the safety and well-being of the clinicians involved. This study aimed to explore the experiences of Swedish ambulance clinicians when encountering threats and violence during their work.

View Article and Find Full Text PDF

Deep learning (DL) has proven to be important for computed tomography (CT) image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain in practice. Diffusion models offer unsupervised means of solving a wide range of inverse problems via posterior sampling.

View Article and Find Full Text PDF