Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Stefan Huwer

Thorsten Feiweier

David Andrew Porter

Mathias Nittka

Thorsten Speckner

Sultan Haider

Josef Pfeuffer

Tony Hyun Kim

Zhigen Zhao

Karin Auslender

Joshua Shiloh Alden

Beatriz Fusaro Guimaraes

In a method and computer for visualizing a medical image data set, in particular a magnetic resonance image data set, the medical imaging data set is provided to the computer which determines a first subset of the medical image data set related to a first parameter and a second subset of the medical image data set related to a second parameter. A first color is assigned to the first subset and a second color is assigned to the second subset. The first subset is transferred to a display in a first color presentation using the first color and the second subset is transferred in a second color presentation using the second color. The first color presentation and the second color presentation are combined for visualizing the medical imaging data set.

Method and system for visualizing a medical image data set

In a method and computer and magnetic resonance (MR) apparatus for classifying MR measurement data acquired from an object under examination by execution of an MR fingerprinting method, wherein the MR measurement data include multiple MR signal profiles acquired by the MR fingerprinting method. At least one texture parameter is derived from the MR measurement data. The MR measurement data are classified into at least one tissue class using the at least one texture parameter. The classified MR measurement data are provided as an output.

Method and apparatus for classifying magnetic resonance measurement data acquired from an examination object using a magnetic resonance fingerprinting method

In a magnetic resonance (MR) method and apparatus, MR signals are acquired in multiple diffusion measurements using a defined set of parameters in the respective measurements that differ in terms of at least one MR parameter from measurement-to-measurement, thereby producing a measured MR signal dataset. Multiple calculated datasets are calculated using a model, with a defined number of model parameters in each calculated dataset, but in different combinations, with each calculated dataset having an MR signal intensity. The measured MR signal having a closest match to the measured MR signal dataset, using a quality criterion based on the MR signal intensity, is identified, and the diffusion parameter is obtained from the calculated dataset having the closest match.

Method and magnetic resonance apparatus for determining diffusion parameters

In a method and magnetic resonance (MR) apparatus for time-dependent intensity correction of diffusion-weighted MR images that are acquired with a sequence of different diffusion gradient fields, different diffusion gradient fields are associated with at least one group, with the association with groups being established so that the diffusion gradient fields that are associated with the same group satisfy an orthogonality criterion. For each group, an MR result image is created from the MR images associated with the group, such that the MR result image has a suppressed direction dependency of the diffusion weighting in comparison to the constituent MR images. An intensity correction can be made based on the multiple MR result images and used to correct the constituent MR images.

Method and magnetic resonance system for time-dependent intensity correction of diffusion-weighted MR images

In a magnetic resonance (MR) method and system for the generation of diffusion information, diffusion-weighted MR images of an examination subject are generated, each image being generated using an individual diffusion gradient. The diffusion gradients, and therefore the MR images, are sorted such that, after the sorting, a predefined number of diffusion gradients respectively forms a group. Each diffusion gradient belongs to at least one of these groups, and the diffusion gradients of the respective same group are all as linearly independent of one another as possible. The MR images whose diffusion gradients form a group are assembled into an MR result image. Spatial transformations between the MR result images are determined, and the MR images are modified using these spatial transformations. The diffusion information is formed with the aid of the modified MR images.

Magnetic resonance system and method to generate diffusion information

In a method for correction of distortions in image data in a diffusion imaging, the image data are acquired with an imaging MRT measurement for a predetermined diffusion weighting and map a predetermined image segment. A diffusion model for the image segment is determined. Output image data are determined for the image segment such that the output image data are essentially free of distortions caused by diffusion weighting. Reference image data are estimated for the predetermined diffusion weighting for the image segment based on the output image data and the diffusion model. The acquired image data are compared with the reference image data and the acquired image data are corrected based on the comparison.

Method and magnetic resonance system to correct distortions in image data

In a method and magnetic resonance apparatus to reduce distortions in magnetic resonance diffusion imaging, a magnetic resonance data acquisition system is operated to acquire magnetic resonance data in a first measurement with a first diffusion weighting, and to acquire magnetic resonance data in a second measurement with a second, different diffusion weighting. A non-linear, system-specific distortion-correcting function is determined on the basis of system-specific information that is specific to said magnetic resonance data acquisition system. Correction parameters are calculated to correct distortions in subsequently-acquired diffusion-weighted magnetic resonance images, based on the data acquired in the first and second measurements with the system-specific distortion-correcting function applied thereto. The subsequently-acquired diffusion-weighted magnetic resonance images are corrected using the correction parameters to at least reduce distortions therein.

Method and magnetic resonance system to reduce distortions in diffusion imaging

In a method and system to generate magnetic resonance (MR) images by MR data are acquired by a pure phase-coded imaging in k-space having a predetermined set of possible measurement points, with the MR data being acquired only for a predetermined subset of the measurement points of this set. An image is reconstructed from the acquired measurement points of the subset such that information about un-acquired measurement points of the set is also obtained.

Magnetic resonance pre-determined data acquisition and image reconstruction with location-coding of magnetic resonance data exclusively via phase coding only

In a method and magnetic resonance (MR) system for correction of image distortions that occur in acquisitions of diffusion-weighted MR images of an examination subject a first adjustment measurement with a first diffusion weighting is implemented, a second adjustment measurement with a second diffusion weighting is implemented and correction parameters to de-skew diffusion-weighted MR images are automatically calculated in a computer on the basis of the two adjustment measurements. One of the two adjustment measurements is implemented with a predetermined diffusion weighting in three orthogonal diffusion directions, and correction parameters are determined for the three orthogonal diffusion directions.

Magnetic resonance method and apparatus to reduce distortions in diffusion imaging

A method is disclosed for acquiring and displaying image data, in particular MR image data. In at least one embodiment, the method includes scanning an examination object by way of a magnetic resonance imaging scanner and generating first (MR) image data of the examination object, wherein scanning parameters during the scan are selected such that the regions of interest in the scanned examination object have high image data values, and the regions which are not of interest in the examination object have, relative thereto, low image data values in the first MR image data; generating a mask on the basis of the first image data by means of which mask regions in the first MR image data which have the low image data values can be hidden; scanning the examination object by way of a medical imaging system and generating second image data of the examination object; applying the mask to the first and/or second image data; and displaying the first and/or second image data processed by the mask.

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Erlangen, Germany

Stefan Huwer