Siemens Aktiengesellschaft

Siemens Aktiengesell Schaft

Ernst Klotz

Herbert Bruder

Rainer Raupach

Thomas Flohr

Karl Stierstorfer

Bernhard Schmidt

Bernhard Geiger

Grzegorz Soza

Christophe Chefd'hotel

Ute Feuerlein

Stefan Schaller

Martin Petersilka

Hendrik Ditt

Harald Schöndube

Matthias Niethammer

Annabella Rauscher

Corinna Bürger

Jochen Schleu

In an embodiment of the invention, a plurality of images of a region under examination are recorded at different times. Anatomical information and flow information are derived from the images. The anatomical information may relate to the course of vessels or the structure of perfused tissue. The temporal component of the flow information can advantageously be combined with the anatomical information in a resultant image. An intensity-dependent fenestration assigns a gray-scale value to pixels of the resultant image in accordance with the anatomical information. A time-dependent fenestration assigns a chromaticity to the pixels of the resultant image in accordance with the flow information and the gray-scale values and the chromaticities are assigned independently of one another. Intensity-dependent fenestration is combined with time-dependent fenestration so that chromaticities and gray-scale values are independent of one another and the anatomical information and the flow information are depicted undistorted in the resultant image.

Method for determining a resultant image, computer program, machine-readable data carrier and imaging device

A method is disclosed for the reconstruction of image data of an examination object from measurement data. First and second image data are reconstructed from the measurement data with a first and second respective image characteristic, with an enhanced signal-to-noise ratio of the second image characteristic relative to the first image characteristic. Enhanced image data is calculated using an iterative algorithm using the first and the second image data. In the case of the iterative algorithm, a low pass is applied to a difference between the first image data and the image data of an iteration cycle, and a high pass to a difference between the second image data and the image data of the iteration cycle.

Method for iterative image reconstruction for bi-modal CT data

A method and system for data dependent multi phase image visualization, includes: acquiring a plurality of series of image data acquisitions; registering the plurality of series of image data acquisitions to a same reference series to create a plurality of registered series; combining information from the registered series to create a new series; creating a further new series by a selection decision based on combination rules from information from the plurality of registered series and the new series; and displaying the further new series.

Method and system for data dependent multi phase visualization

In a method and x-ray device to adapt the width and the position of a central value of a greyscale windowing for imaging with the x-ray device based on CT values determined with said x-ray device, the adaptation takes place within the scope of a determination and adjustment of an acquisition tube voltage of an x-ray tube of the x-ray device for an examination of a defined tissue of a patient, assuming a reference tube voltage for the examination of the defined tissue of the patient, and in which a width and position of a central value of the greyscale windowing that are associated with the reference tube voltage are automatically adapted to the acquisition tube voltage.

Method and X-ray device for adapting greyscale windowing

A method for distinguishing between gray matter and white matter starting from a time-dependent computed tomography image data record from a perfusion CT examination is disclosed. In at least one embodiment, a plurality of time-independent images are calculated from the time-dependent image data record, a plurality of threshold histogram analyses are performed in order to determine regions of the brain which can be assigned to one or more types of cerebral matter, and subsequently the region of gray matter is determined from the information obtained in respect of type and region of the cerebral matter using at least one logical combination and at least one exclusion method. A control and computational unit is also disclosed with a storage medium in which a computer program or program module is stored, which executes the described method during operation.

Method for distinguishing between gray matter and white matter and CT system for carrying out the method

A method is disclosed for forecasting the contrast medium flow in a living body, in particular in a patient, in which a defined test bolus with a contrast medium is injected, preferably intravenously and with a known injection flow profile, into the body, preferably into a blood vessel. The time concentration profile of the contrast medium is observed and determined over a limited time period with a number of measuring instants at at least one location in the body with the aid of a tomographic method. The time profile of the contrast medium concentration of another contrast medium dose is forecast with the aid of a linear cause/effect formulation from the measured data obtained via the distribution of the contrast medium. The following calculation formula is then used for forecasting the time concentration profile {tilde over (c)}(t) of the contrast medium at at least one of the previously measured locations of the body: 

Method for forecasting the contrast medium flow in a living body

A method is for calibration of perfusion parameter images. The image data from tomographic imaging measurements are analyzed using a perfusion model, and perfusion parameter values obtained from the analysis are calibrated with a calibration factor to a physiological normal value. To perform the calibration, an image area which contains several different tissue compositions, and in which approximately normal perfusion conditions can be assumed, is selected from the obtained perfusion parameter image. A frequency analysis of the perfusion parameter values contained in this image area is then performed, and at least one frequency interval is selected which corresponds at least approximately to a frequency interval of the occurrence of perfusion parameter values of a known tissue composition. A mean value is calculated from the perfusion parameter values in the frequency interval, and a comparison with the physiological normal value for this tissue composition is made in order to determine the calibration factor or a calibration value included in the calibration factor. The method permits automatic or substantially automatic calibration of perfusion parameter images.

Method for automatic calibration of perfusion parameter images

A method is disclosed for a multislice computer assisted tomograph, capable of carrying out a spiral scan of an object volume with a pitch p selected to be small enough that each slice of the object volume is multiply detected during the spiral scan. The method includes calculating, using measured data of two temporally consecutive at least one of revolutions and half revolutions, an image of the object volume from which a change inside the object volume between the two temporally consecutive at least one of revolutions and half revolutions is directly visible. An embodiment of the method can permit, for example, the detection and visualization of dynamic processes with an enhanced time resolution.

Method for detecting and visualizing dynamic processes in an object volume

In a method and apparatus for image processing proceeding from a computed tomography (CT) image of a lung as an original image that is registered using a contrast agent, pulmonary parenchyma pixels are determined, the pulmonary parenchyma pixels are presented in false colors, and the remaining image regions are presented in the gray scale values of the original image.

Method and apparatus for processing a computed tomography image of a lung obtained using contrast agent

In a method for examining a living subject with an imaging method making use of the concentration of a contrast agent having a physical property that is identifiable with the imaging method in a region of interest (ROI) of the subject presented in time-successive images acquired with the imaging method representing quantitative values of the physical property, a histogram of the quantitative values of the physical property in the ROI is produced for each of the individual images, and the contrast agent concentration in the ROI is determined on the basis of the frequency of occurrence of the quantitative values of the physical property in the ROI.

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Uttenreuth, Germany

Ernst Klotz