Objective: We develop optimization-based algorithms to accurately reconstruct multiple ( 2) basis images directly from dual-energy (DE) data in CT.
Methods: In medical and industrial CT imaging, some basis materials such as bone, metals, and contrast agents of interest are confined often spatially within regions in the image. Exploiting this observation, we develop an optimization-based algorithm to reconstruct, directly from DE data, basis-region images from which multiple ( 2) basis images and virtual monochromatic images (VMIs) can be obtained over the entire image array.
Results: We conduct experimental studies using simulated and real DE data in CT, and evaluate basis images and VMIs obtained in terms of visual inspection and quantitative metrics. The study results reveal that the algorithm developed can accurately and robustly reconstruct multiple ( 2) basis images directly from DE data.
Conclusions: The developed algorithm can yield accurate multiple ( 2) basis images, VMIs, and physical quantities of interest from DE data in CT.
Significance: The work may provide insights into the development of practical procedures for reconstructing multiple basis images, VMIs, and physical quantities from DE data in applications. The work can be extended to reconstruct multiple basis images in multi-spectral or photon-counting CT.
Introduction And Objectives: Isolated hypogonadotropic hypogonadism (IHH) may be associated with pituitary gland and olfactory system disorders. We aimed to correlate findings of Magnetic Resonance Imaging (MRI) of the pituitary gland and olfactory system in IHH patients with the patients' olfactory phenotype.
Patients And Methods: The present research was a single-center retrospective case-control study.
Background: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (IGRI) systems, are susceptible to disruptions in patients' respiratory rhythm due to factors such as pain and psychological distress.
Methods: We developed an IGRI system with a coded structured light camera and a binocular camera. Our system incorporates dual-pathway deep learning networks, combining convolutional long short-term memory (ConvLSTM) and point long short-term memory (PointLSTM) modules for real-time respiratory signal monitoring.
Lipid droplets frequently form contact sites with the membrane of the vacuole, the lysosome-like organelle in yeast. These vacuole lipid droplet (vCLIP) contact sites respond strongly to metabolic cues: while only a subset of lipid droplets is bound to the vacuole when nutrients are abundant, other metabolic states induce stronger contact site formation. Physical lipid droplet-vacuole binding is related to the process of lipophagy, a lipid droplet-specific form of microautophagy.
Although several antithrombotic strategies have been investigated for the management of cryptogenic strokes, ie, ischemic strokes without known etiologies, an optimal antithrombotic strategy for cryptogenic strokes is unknown. We aim to assess oral antithrombotic agents' comparative efficacy and safety after cryptogenic stroke to identify an optimal treatment.A systematic review and meta-analysis synthesizing evidence from randomized controlled trials (RCTs) obtained from PubMed, Embase Cochrane, Scopus, and Web of Science until February 2024.
Understanding the goal of an observed action requires computing representations that are invariant to specific instantiations of the action. For example, we can accurately infer the goal of an action even when the agent's desired outcome is not achieved. Observing actions consistently recruits a set of frontoparietal and posterior temporal regions, often labeled the "action observation network.
