Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Healthineers Ag

Siemens Medical Solutions USA, Inc.

Bayer Pharma Aktiengesellschaft

Bernhard Schmidt

Thomas Flohr

Martin Sedlmair

Rainer Raupach

Thomas Allmendinger

Bernhard Krauss

Katharine Lynn Rowley Grant

Michael Grasruck

Grzegorz Soza

Philipp Hoelzer

Matthias Lichy

Karl Stierstorfer

Steffen Kappler

Bernd Hofmann

Bernhard Krauβ

Andreas Mahnken

Christine Bach

Reinhard Schneider

Xavier Battle

Sebastian Schmidt

Herbert Bruder

Tong Fang

Michael Scheuering

Michael Suehling

Christian Hofmann

Yunqiang Chen

Ute Feuerlein

Stefan Schaller

Willi A Kalender

Sandra Sudarsky

Hasan Ertan Cetingul

Andreas Krauss

Jing Yan

Gregor Jost

Hubertus Pietsch

Harald Schöndube

Ernst Klotz

Michael Sühling

Peter Huber

Mark-Aleksi Keller-Reichenbecher

Eric Fournie

Klaus Indefrey

Rainer Grimmer

Markus Juergens

Stefan Kaepplinger

Tristan Nowak

Dieter Boeing

Jürgen Stoll

Hans-Christoph Becker

Indraneel Borgohain

Marcus Wagner

Marc Kachelrieβ

Juergen Stoll

Magdalini-Charikleia Pilatou

Rüdiger Lawaczeck

Friederike Schoeck

Philip Stenner

Katharine Grant

Marcus Brehm

Claudia Lindner

Bernhard Krauß

A method for determining a quantitative result CT parameter map in a region of interest of an object under examination is described. The method includes acquiring a sequence of quantitative input CT parameter maps for at least two predetermined times, the sequence being generated by a contrast-enhanced spectral multiphase CT of the region of interest; receiving a sequence of contrast-enhanced MRI image datasets, the MRI datasets having a higher temporal resolution than the sequence of input CT parameter maps; determining a relation between the MRI image datasets and the input CT parameter maps; and determining the result CT parameter map based on the determined relation and the MRI image datasets for at least one additional time, the at least one additional time being different from the predetermined time.

Multimodal determination of an augmented sequence of CT parameter maps

A first image data set and at least one second image data set are captured, and a contrast-enhanced image data set and a non-contrast image data set are determined based on the first and the at least one second image data set. The perfusion image data set is calculated based on a ratio of image values of the contrast-enhanced image data set and locally corresponding image values of the non-contrast image data set, and the perfusion image data set is provided via a second interface.

Method and apparatus for providing a perfusion image data set of a patient

At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.

Computer-implemented method for evaluating an angiographic computed tomography dataset, evaluation device, computer program and electronically readable data medium

A system and method include acquisition of a two-dimensional radiograph of a patient, input of the radiograph to a trained machine learning model to generate a classification, performance of a computed tomography scan of the patient based on the two-dimensional radiograph if the classification indicates that the patient does not have a first condition, and determination to modify the computed tomography scan if the classification indicates that the patient has the first condition.

Machine learning-assisted computed tomography workflow

An imaging method is described for generating image data of an examination region of an object that is to be examined. First X-ray projection measurement data of the examination region is acquired using a first X-ray energy spectrum and at least second X-ray projection measurement data of the examination region is acquired using a second X-ray energy spectrum which is different from the first X-ray energy spectrum. A priori image data is reconstructed based on at least the first X-ray projection measurement data and a location-dependent distribution of X-ray attenuation values. A basis material decomposition is performed based on the first X-ray projection measurement data and the at least second X-ray projection measurement data. A location-dependent weighting of the basis materials is determined as a function of the location-dependent distribution of the X-ray attenuation values. An image for the examination region is determined by reconstructing virtual basis-material-weighted image data.

Generating X-ray image data on the basis of a weighting of basis materials varying depending on location

One or more example embodiments provides a method for evaluating an angiographic dual-energy computed tomography dataset recorded using a contrast agent comprising iodine to determine a quantitative calcium score.

Method for evaluating an angiographic dual-energy computed tomography dataset, evaluation facility and non-transitory electronically readable data carrier

A method is for noise reduction in image recordings. In an embodiment, the method includes providing an input image; de-noising the input image and producing a de-noised input image; and adapting noise texture of pixels of the de-noised input image via an adaptation method, noise amplitude of the de-noised input image being largely retained and the noise texture of the pixels of the de-noised input image being adapted to correspond largely to a defined noise texture. A corresponding device, a production method for an adaptation device, such an adaptation device, and a control facility and a computed tomography system are also disclosed.

Method and device for noise reduction in image recordings

In one embodiment, a method is for calculating an examination parameter for a computed tomography examination of an area of interest of a patient. The method includes receiving a topogram of the area of interest of the patient; determining fat distribution information by applying a trained machine learning algorithm onto the topogram; and calculating the examination parameter for the computed tomography examination of the area of interest of the patient based on the fat distribution information.

Topogram-based fat quantification for a computed tomography examination

An analysis method is for automatically determining radiological result data from radiology data sets. In an embodiment, the method includes provisioning a first radiology data set at least based on X-ray data of a first X-ray energy spectrum; provisioning at least one second radiology data set at least based on X-ray data of a second X-ray energy spectrum; provisioning an analysis unit including a neural network, to analyze radiology data sets including an input layer with a plurality of cells, a number of intermediate layers and an output layer representing a radiological result; analyzing the first radiology data set and the at least one second radiology data set, at least subsets of the first radiology data set and the at least one second radiology data set being assigned to different cells of the input layer for joint processing in the neural network; and acquiring result data on the output layer.

Analysis method and analysis unit for determining radiological result data

One embodiment relates to a method for providing image data of a hollow organ. The method includes applying a first contrast agent to a lumen of the hollow organ, to obtain a contrast agent filling of the lumen; applying a second contrast agent to a blood vessel system, the blood vessel system supplying a wall of the hollow organ, the second contrast agent having a different absorption spectrum than the first contrast agent; generating spectrally resolved computed tomography data of an examination area, the examination area including the hollow organ; calculating first image data indicative of a presence of the first contrast agent and second image data indicative of a presence of the second contrast agent by applying a material separation algorithm onto the spectrally resolved computed tomography data; and providing the image data of the hollow organ including the first image data and the second image data.

Method for providing image data of a hollow organ

An embodiment relates to a computer-implemented method for generating a combined tissue-vessel representation. The method includes receiving imaging data of a tissue; receiving imaging data of a vessel; generating a tissue representation based on the imaging data of the tissue; generating a vessel representation based on the imaging data of the vessel; and generating a combined tissue-vessel representation based on the vessel representation and the tissue representation, the vessel representation being overlaid over the tissue representation.

Method and computer system for generating a combined tissue-vessel representation

A method is for metal artifact reduction in CT image data, the CT image data including multiple 2D projection images acquired using different projection geometries and suitable to reconstruct a 3D image data set of a volume of an imaged object. In an embodiment, the method includes a metal artifact reduction process including at least, acquiring, using a multi-energy CT technique, energy-resolved CT image data associated with multiple energy ranges. At least one result of the multi-energy technique is used in at least one aspect of the metal artifact reduction process.

Multi-energy metal artifact reduction

A method is for the characterization of plaque in a region of interest inside an examination subject by way of a plurality of image data sets. The image data sets have been reconstructed from a plurality of projection data sets, which have been acquired via a CT device using different X-ray energy spectra. The method includes: acquiring the image data sets, which include a plurality of pixels. Spectral parameter values are acquired on a pixel by pixel basis using at least two image data sets. Character parameter values are then acquired on a pixel by pixel basis to characterize plaques on the basis of the spectral parameter values. An analysis unit and a computed tomography system are also disclosed.

Characterization of plaque

A method is for producing a CT image data set via a detection unit with a photon-counting X-ray detector and configured to convert detected X-rays into measurement signals resolved at least into a first and a second energy range and, via an X-ray source unit, configured to emit X-rays having a first energy spectrum and having a different second energy spectrum. The method includes adapting the first and the second energy ranges, at least one limiting energy of each energy range being adapted; emitting X-rays of the first and second energy spectrum; detecting the emitted X-rays, at least one measurement signal being generated as a function of each respective energy range and the respective energy spectrum; producing the spectral CT image data set based upon the generated first and second measurement signals with the assistance of a spectral image processing technique; and outputting the spectral CT image data set.

Method and apparatus for producing a spectral computed tomography image data set

A method and system are for analyzing an anatomical structure of interest in 3D image data. In an embodiment, the method includes segmenting a first contour of the structure of interest in the 3D image data, the first contour defining a first segmented contour volume within the 3D image data; generating a first 2D pattern based on at least a portion of the surface of the first contour or based on at least a portion of the first segmented contour volume; performing a texture analysis on the first 2D pattern; and outputting a texture analysis information.

Method and system for evaluation of tumor tissue by unfolding morphological and texture properties

Growing community of inventors

Fuerth, Germany

Bernhard Schmidt