Abstract: The present invention relates to a low-temperature additive for fuel oils having a sulfur content of less than 50 ppm, comprising i) at least one oil-soluble amide-ammonium salt of a polycarboxylic acid with a mono- and/or dialkylamine (A) and ii) 5-100% by weight, based on the amount of amide-ammonium salt (A), of an oil-soluble amine (B), and iii) 0.1 to 10 parts by weight, based on the amount of amide-ammonium salt (A), of a resin formed from at least one aromatic compound bearing an alkyl radical and an aldehyde and/or ketone (D).

Abstract: It is an object of the invention to provide a heat-resistant vacuum insulation panel having two heat-resistant protective layers to improve fire protection, in particular at locations of the vacuum insulation panel subject to mechanical stress.

Abstract: A method is for computed tomography imaging. In an embodiment, the method includes provisioning a CT data set of an object, the CT data set being previously recorded via a multispectral recording method; suppressing a contrast, caused by a tissue type, and generating a contrast-suppressed data set from the CT data set provisioned; and analyzing at least the contrast-suppressed data set generated or a data set generated via a machine learning algorithm based on the contrast-suppressed data set, the analyzing being configured to identify at least one change in the tissue type. A corresponding device, a control device for a computed tomography system or a diagnosis system, and a diagnosis system and a computed tomography system are also disclosed.

Abstract: A method is for providing decision-supporting data. In an embodiment, the method includes receiving photon-counting computed tomography data relating to an examination region; determining a location of a thrombus in the examination region, based on the photon-counting computed tomography data received; generating the decision-supporting data, relating to at least one of the thrombus and a vascular wall in a region of the thrombus, based on the photon-counting computed tomography data received and the location of the thrombus determined; and providing the decision-supporting data generated.

Abstract: A method is for actuating a medical imaging device for generating a second three-dimensional image dataset including a target region in a region of interest of a patient with a functional impairment. The method includes providing a first three-dimensional image dataset including the region of interest of the patient; identifying the target region based on the first three-dimensional image dataset, a partial region of the region of interest with the functional impairment being determined; determining an imaging parameter for generating the second three-dimensional image dataset based on the identified target region; and actuating the medical imaging device based on the imaging parameter for the generation of the second three-dimensional image dataset.

Abstract: A method is for actuating a medical imaging device for generating a second three-dimensional image dataset including a target region in a region of interest of a patient with a functional impairment. The method includes providing a first three-dimensional image dataset including the region of interest of the patient; identifying the target region based on the first three-dimensional image dataset, a partial region of the region of interest with the functional impairment being determined; determining an imaging parameter for generating the second three-dimensional image dataset based on the identified target region; and actuating the medical imaging device based on the imaging parameter for the generation of the second three-dimensional image dataset.

Abstract: A method is for computed tomography imaging. In an embodiment, the method includes provisioning a CT data set of an object, the CT data set being previously recorded via a multispectral recording method; suppressing a contrast, caused by a tissue type, and generating a contrast-suppressed data set from the CT data set provisioned; and analyzing at least the contrast-suppressed data set generated or a data set generated via a machine learning algorithm based on the contrast-suppressed data set, the analyzing being configured to identify at least one change in the tissue type. A corresponding device, a control device for a computed tomography system or a diagnosis system, and a diagnosis system and a computed tomography system are also disclosed.

Abstract: A method is for providing decision-supporting data. In an embodiment, the method includes receiving photon-counting computed tomography data relating to an examination region; determining a location of a thrombus in the examination region, based on the photon-counting computed tomography data received; generating the decision-supporting data, relating to at least one of the thrombus and a vascular wall in a region of the thrombus, based on the photon-counting computed tomography data received and the location of the thrombus determined; and providing the decision-supporting data generated.

Abstract: The left ventricle epicardium is estimated in medical diagnostic imaging. C-arm x-ray data is used to detect an endocardium at different phases. The detected endocardium at the different phases is compared to sample endocardiums at different phases. The sample endocardiums have corresponding sample epicardiums. The transformation between the most similar sample endocardium or endocardiums over time and the detected endocardium over time is applied to the corresponding sample epicardium or epicardiums. The transformed sample epicardium over time is the estimated epicardium over time for the C-arm x-ray data.

Abstract: A 3D result image of an object is reconstructed from a set of X-ray two-dimensional projections of the object. A 3D reference image of the object is reconstructed by employing a compressed sensing technique based on at least some of the 2D projections at a reference motion state of the object. By employing an algebraic and/or analytic reconstruction technique, 3D intermediate images are reconstructed for various motion states of the object. The 3D intermediate images are registered with the 3D reference image to obtain spatial transformations for the various motion states of the object. Based on the spatial transformations, the 3D intermediate images are transformed to a joint phase and combined to obtain the 3D result image.

Abstract: Background information is subtracted from projection data in medical diagnostic imaging. The background is removed using data acquired in a single rotational sweep of a C-arm. The removal may be by masking out a target, leaving the background, in the data as constructed into a volume. For subtraction, the masked background information is projected to a plane and subtracted from the data representing the plane.

Abstract: A 3D result image of an object is reconstructed from a set of X-ray two-dimensional projections of the object. A 3D reference image of the object is reconstructed by employing a compressed sensing technique based on at least some of the 2D projections at a reference motion state of the object. By employing an algebraic and/or analytic reconstruction technique, 3D intermediate images are reconstructed for various motion states of the object. The 3D intermediate images are registered with the 3D reference image to obtain spatial transformations for the various motion states of the object. Based on the spatial transformations, the 3D intermediate images are transformed to a joint phase and combined to obtain the 3D result image.

Abstract: Background information is subtracted from projection data in medical diagnostic imaging. The background is removed using data acquired in a single rotational sweep of a C-arm. The removal may be by masking out a target, leaving the background, in the data as constructed into a volume. For subtraction, the masked background information is projected to a plane and subtracted from the data representing the plane.

Abstract: The left ventricle epicardium is estimated in medical diagnostic imaging. C-arm x-ray data is used to detect an endocardium at different phases. The detected endocardium at the different phases is compared to sample endocardiums at different phases. The sample endocardiums have corresponding sample epicadriums. The transformation between the most similar sample endocardium or endocardiums over time and the detected endocardium over time is applied to the corresponding sample epicardium or epicardiums. The transformed sample epicardium over time is the estimated epicardium over time for the C-arm x-ray data.