Siemens Healthcare Gmbh

Siemens Healthineers Ag

Siemens Aktiengesellschaft

The Johns Hopkins University

Mario Zeller

Dominik Paul

Flavio Carinci

Himanshu Bhat

Adam Kettinger

Nadine Dispenza

David Grodzki

Manuel Stich

Pedro Miguel Itriago Leon

Thorsten Feiweier

Andreas Greiser

Thomas Beck

Josef Pfeuffer

Kun Zhou

Wilhelm Horger

Michael Köhler

Rene Kartmann

Uvo Hoelscher

Markus Vester

Yan Zhang

Mathias Nittka

Sultan Haider

Hans-Peter Fautz

Matthias Gebhardt

Rainer Schneider

Johann Sukkau

Lars Lauer

Vibhas S Deshpande

Ralf Kartäusch

Daniel Rinck

Carmel Hayes

Esther Raithel

Gudrun Ruyters

Dingxin Wang

Jan Fritz

Mathias Blasche

Ralf Kartaeusch

Kuan Jin Lee

Gerald Mattauch

Miriam Van De Stadt-Lagemaat

Hannah Hale

Max Müller

Christian Meixner

According to a method, first magnetic resonance signals are captured at a first time point. Second magnetic resonance signals are captured at a second time point. The first magnetic resonance signals are provoked by nuclear spin excitations of fat and water in an examination object. The second magnetic resonance signals are provoked by nuclear spin excitations of fat and water in the examination object. The nuclear spin excitations of fat and water are in phase at the first time point. The nuclear spin excitations of fat and water are in opposed phase at the second time point. A Bfield map is determined based on the first magnetic resonance signals and the second magnetic resonance signals. Further magnetic resonance signals are captured. At least one magnetic resonance mapping is determined by reconstructing the further magnetic resonance signals. The at least one magnetic resonance mapping is corrected based on the Bfield map.

Method for correcting a magnetic resonance mapping

A module for use in a magnetic resonance apparatus, a system, and a method for predicting a potential failure of a module are provided. The module includes at least one sensor configured to detect values of at least one module parameter of the module. The module parameter, such as detected values thereof, is suitable for predicting a potential failure of the module on the basis thereof.

Predicting a potential failure of a module for use in a magnetic resonance apparatus

A method for driving a MRI system to generate MRI data of an examination subject may include performing an accelerated echoplanar imaging with an undersampling according to a pulse sequence diagram to acquire k-space data. The pulse sequence diagram may have a plurality of repetitions respectively including: a first sampling diagram configured for an acquisition of k-space data for Nyquist ghost correction, or to generate magnetic field maps, a subsequent second sampling diagram configured for an accelerated echoplanar acquisition, and an excitation diagram that is common to both acquisitions. The first sampling diagram of a real subset of the plurality of repetitions may be modified to: supplement the acquired k-space data using a supplementation of k-space data missing due the undersampling, and/or correct image space of artifacts occurring due to the undersampling based on the k-space data acquired with the modified first sampling diagram.

Method and device for driving a magnetic resonance imaging system

A method for avoiding artifacts in measurement data captured using a magnetic resonance system which has a gradient unit. The method includes loading data which characterizes the gradient unit of the magnetic resonance system; loading a measurement protocol to be used for capturing the measurement data, wherein the measurement protocol includes gradients to be switched and RF excitation pulses and RF refocusing pulses to be irradiated, wherein, after irradiation of an RF excitation pulse, a train of at least two RF refocusing pulses is irradiated and measurement data is captured after each RF refocusing pulse; determining compensation gradients which, after the capture of the measurement data, are to be switched after a final RF refocusing pulse of the train of RF refocusing pulses associated with the RF excitation pulse and before a following RF excitation pulse as a function of the loaded measurement protocol and of the data which characterizes the gradient unit; and carrying out the measurement protocol using the determined compensation gradients.

Avoidance of artifacts in measurement data captured using a magnetic resonance system

A method for avoiding artifacts in image data reconstructed from measurement data acquired by means of a TSE (turbo spin echo) sequence with a coil having a plurality of antenna elements associated with one channel respectively. The method includes loading the measurement data, acquired with the coil, of all channels of the coil; loading at least the first three echo signals respectively of an echo train from phase correction measurement data of all channels acquired with the coil in relation to the TSE sequence; determining a step value d for each channel of the coil from the loaded phase correction measurement data, which value describes a signal drop in the three successive echo signals of the phase correction measurement data; channel-by-channel manipulation of the measurement data as a function of the step value of the respective channel; and reconstructing image data by taking into account the manipulated measurement data.

Avoiding artifacts in image data reconstructed from measurement data acquired by means of a turbo spin echo sequence

Permitted gradient intensities are established to prevent an overloading of a gradient unit of a magnetic resonance system during a recording, with the magnetic resonance system, of scan data from an examination object situated in a scan volume of said magnetic resonance system.

Establishing permitted gradient intensities to prevent overloading of a magnetic resonance (MR) system gradient unit

In method for MR imaging, an MR signal is acquired for each of a plurality of readout gradient pulses during a respective readout period and an MR image is generated on the basis thereof. A start time of the respective readout period relative to a start time of the respective readout gradient pulse is delayed by a delay duration which is selected randomly or pseudo-randomly from two or more predefined time values, and/or to generate the MR image, the acquired MR signals are processed, wherein the processing includes a frequency conversion based around a center frequency which is randomly or pseudo-randomly selected from two or more predetermined frequency values.

Method for magnetic resonance imaging, magnetic resonance imaging system and computer program product

In a method for determining a fat-reduced MR image, a first MR image is provided having, apart from the other tissue constituents, MR signals from only one of the two fat constituents, the first MR image is applied to a trained ANN, which was trained by first MR training data as the input data, the training data including, apart from the other tissue constituents, MR signals from only the one of the two fat constituents, and using second MR training data as a base knowledge, the second MR training data including, apart from the other tissue constituents, no MR signals from the two fat constituents; and an MR output image is determined from the trained ANN, to which the first MR image was applied, as a fat-reduced MR image, wherein the fat-reduced MR image includes, apart from the other tissue constituents, no MR signals from the two fat constituents.

Fat suppression using neural networks

A method for preparing magnetic resonance imaging of an object under examination is described. A plurality of representative pulse sequence segments are generated, each of which is associated with a reference gradient amplitude of the gradient pulse having the highest stimulation potential of the representative pulse sequence segment, and the stimulation potential of which is representative of a group of partially different pulse sequences. For each of the representative pulse sequence segments, a maximum gradient slew rate is determined for which a permitted maximum value of the stimulation potential is not exceeded. One of the representative pulse sequence segments is determined and selected, for a measurement protocol to be planned for a magnetic resonance imaging to be performed, according to the gradient amplitude of the gradient pulse having the highest stimulation potential of a pulse sequence segment of the pulse sequence on which the measurement protocol is based. The pulse sequence segment of the pulse sequence on which the measurement protocol is based is adjusted in such a way that a maximum gradient slew rate associated with the selected representative pulse sequence segment is also not exceeded by the pulse sequence segment of the pulse sequence on which the measurement protocol is based.

Preparing a magnetic resonance imaging method in compliance with stimulation-based limitations

A method for creating calibration data for processing accelerated measurement data of an object to be examined using a magnetic resonance system. The method includes recording measurement data sets using an acquisition acceleration method, recording calibration data sets, and determining processed measurement data sets from the accelerated measurement data sets using the calibration data sets so that effects of the acquisition acceleration method used are eliminated in the processed measurement data sets. The recording of the calibration data sets includes an application of at least one attenuation method for attenuating signals causing phase errors.

Creating calibration data for processing recorded measurement data of an object to be examined using an MR system

According to a method, first MR reference data and first MR imaging data are captured. Further MR imaging data is then captured. The capturing includes in each case generating at least one excitation pulse with a transmit coil of the magnetic resonance apparatus and irradiating the at least one excitation pulse into a patient receiving region, generating MR signals in a generation region using the at least one excitation pulse, and receiving the MR signals as MR data with a receive coil. A degree of difference that describes a difference between the generation region on capture of the first MR reference data and the generation region on capture of the further MR imaging data is determined. MR reference data is provided as a function of the degree of difference. An MR image is reconstructed based on the captured further MR imaging data and the provided further MR reference data.

Method for capturing MR data

A method is for acquiring a magnetic resonance (MR) image dataset of at least two slices via simultaneous multi-slice excitation. An embodiment of the method includes executing an MR imaging sequence using multi-band radio-frequency excitation pulses to excite the at least two slices simultaneously in at least two repetitions, the repetitions each being executed according to a phase modulation scheme in which each of the simultaneously excited slices is assigned a phase and the phase of at least one of the simultaneously excited slices is changed from one repetition to the next, thereby acquiring an MR dataset of a collapsed image in each repetition; performing a spatial registration between the at least two collapsed images and performing motion correction on at least one of the MR datasets of the collapsed images; and reconstructing MR images of the at least two slices from the corrected MR datasets of the collapsed images.

Method for acquiring an MR-image dataset of at least two slices by means of simultaneous multislice excitation

In a method for determining at least one test position for a test measurement to be recorded by means of a magnetic resonance system, a test image is recorded, and at least one test position is selected based on the test image. With methods for the compensation of effects of deviations of gradients actually generated during a readout duration from gradients planned for this readout time duration, the selection of test positions according to the disclosure based on a test image advantageously ensures that the test positions lie in a recording region favorable for the test measurement, e.g. also within an examination object to be examined in the test image. A higher image quality in MR images, which were generated using test measurements carried out at test positions positioned according to the disclosure, can therefore be achieved.

Determining test positions in a target volume for a magnetic resonance system test measurement to improve magnetic resonance image quality of the system

In a method for diffusion-weighted MR-imaging of an object, which undergoes a cyclic motion, a first sub-period type of the cyclic motion is predicted for a first acquisition timeframe, where the first sub-period type corresponds to one of two or more predefined characteristic types of sub-periods of the cyclic motion. A first amount of diffusion-weighting may be selected based on the first sub-period type. A first MR-acquisition may be carried out during the first acquisition timeframe, where a diffusion-weighting according to the first amount of diffusion-weighting is applied. An MR-image of the object is generated based on MR-data including a first MR-dataset obtained as a result of the first MR-acquisition.

Magnetic resonance imaging with a dynamic diffusion-weighting

The disclosure relates to techniques for operating an imaging facility for preparing an imaging process. For each imaging process, at least one image dataset is reconstructed in a reconstruction step from raw data recorded in accordance with at least one recording protocol using a reconstruction facility with reconstruction software. For advance calculation of a duration for the reconstruction step, an input dataset comprising at least one protocol parameter of the recording protocol influencing the duration of the reconstruction step and at least one hardware parameter describing the hardware of the reconstruction facility and/or at least one software parameter describing the reconstruction software is compiled, and the duration is ascertained from the input dataset by way of a trained advance calculation function, which is trained by machine learning.

Computer-implemented method for operating an imaging facility, imaging facility, computer program and electronically readable data carrier

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Erlangen, Germany

Mario Zeller