Purpose: Electromagnetic tracking (EMT) has great potential as a quality assurance tool in interstitial brachytherapy. Since its clinical application in most cases comprises a comparison with brachytherapy plan data, EMT registration and plan data are crucial. Registration uncertainties influence EMT outcomes and further decision-making processes.
View Article and Find Full Text PDFPurpose: Respiratory-guided computed tomography (CT) typically employs breathing motion surrogates to feed image reconstruction or visual breathing coaching. Our study aimed to assess the impact of table movements and table sag on the breathing curves recorded in four-dimensional (4D) CT and deep-inspiration breath-hold (DIBH) CT.
Methods: For breathing curve measurements, static and dynamic phantom scenarios were used.
Background: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in RT treatment planning.
Methods: Segment Anything was evaluated in an interactive point-to-mask auto-segmentation task for glioma brain tumor auto-contouring in 16,744 transverse slices from 369 MRI datasets (BraTS 2020 dataset). Up to nine interactive point prompts were automatically placed per slice.
Diving marine mammals are a diverse group of semi- to completely aquatic species. Some species are targets of conservation and rehabilitation efforts; other populations are permanently housed under human care and may contribute to clinical and biomedical investigations. Veterinary medical care for species under human care, at times, may necessitate the use of general anesthesia for diagnostic and surgical indications.
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