A method of processing magnetic resonance (MR) data of a sample under investigation, includes the steps of providing the MR data being collected with an MRI scanner apparatus, and subjecting the MR data to a multi-parameter nonlinear regression procedure being based on a non-linear MR model and employing a set of input parameters, wherein the regression procedure results in creating a parameter map of model parameters of the sample, wherein the input parameters (initial values and possibly boundaries) of the regression procedure are estimated by a machine learning based estimation procedure applied to the MR data. The machine learning based estimation procedure preferably includes at least one of at least one neural network and a support vector machine. Furthermore, an MRI scanner apparatus is described.

The invention relates to a motion determination device for determining the motion of an object. The motion determination device comprises a magnetic resonance (MR) information providing unit (2, 5) for providing an MR image of the object (6) and for providing non-image MR data of the object which have been acquired at different acquisition times, and a motion determination unit (9) for determining a motion field, which describes the motion of the object (6), depending on the provided non-image MR data acquired at the different acquisition times and the provided MR image. Since the non-image MR data, which are preferentially k-space data, are directly used for determining the motion field, i.e. without an intermediate reconstruction of MR images based on the non-image MR data, the motion field can be determined with a very high temporal resolution.

A method for creating a roadmap for a medical workflow includes providing a multidimensional image-dataset including a plurality of images of a predefined organ combined with a number of state-dimensions characterizing a movement state of a moving organ. Measured pilot tone data is provided from a continuous pilot tone signal acquisition. A coordinate is determined for each state-dimension based on the measured pilot tone data, and an image of the multidimensional image-dataset is selected based on the number of determined coordinates of each state dimension.

The invention discloses a method for measuring the intracellular water transmembrane efflux rate (k.sub.io): setting magnetic resonance imaging parameters and measuring the noise level during scanning. Optimizing the flip angle and resetting it through Monte Carlo simulation. Scanning quantitative T1 imaging. Scanning dynamic-contrast-enhanced magnetic resonance imaging and injecting contrast agent. The full shutter speed model (SSM.sub.full) is used to analyze every voxel in the tumor area and obtain the k.sub.io of them. This method significantly improves the accuracy of k.sub.io. The invention discloses the measuring method, system and application of k.sub.io as a magnetic resonance imaging biomarker of glioma, which is not for disease diagnosis, to evaluate the expression level of AQP4. The invention discloses the application of k.sub.io as a magnetic resonance imaging marker of glioma in the preparation of a product for predicting the sensitivity of glioma radiotherapy and chemotherapy. Through the above methods, systems and applications, the non-invasive and quantitative measurement and imaging of AQP4 expression level in glioma have been realized.

A magnetic resonance imaging method is includes collecting spatially encoded data from a subject using an MRI system, and directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data. The method further includes, after directly extracting the number of temporal basis functions, iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data. Finally, the method includes generating a 4D image based on the number of temporal basis functions and the number of coefficient images.

The present invention discloses an analysis method for dynamic contrast-enhanced magnetic resonance image. Firstly, the time-series signal of vascular contrast agent concentration, AIF, of biological individual is obtained from DCE-MRI time-series data. Secondly, perform the nonlinear least sum of square fitting by using the full Shutter-Speed model (SSM.sub.full) and the simplified vascular Shutter-Speed model (SSM.sub.vas) on the DCE-MRI time-series signal of each pixel, and the fitting results of DCE-MRI time-series signal are obtained. Thirdly, the corrected Akaike Information Criterion (AIC.sub.C) score is used to comparing the DCE-MRI time-series signal fitting results to select the optimal model. If the optimal model is SSM.sub.full, distribution maps of five physiological parameters. K.sup.trans, p.sub.b p.sub.o, k.sub.bo, and k.sub.io, are produced after fitting; if the optimal model is SSM.sub.vas, distribution maps of three physiological parameters, K.sup.trans, p.sub.b, and k.sub.bo, are produced after fitting. Finally, perform error analysis on the k.sub.io and k.sub.bo, resulting the final distribution maps of k.sub.io and k.sub.bo along with distribution maps of parameters K.sup.trans, p.sub.b, p.sub.o. This method can improve the estimation accuracy of K.sup.trans, p.sub.b, p.sub.o, k.sub.bo and k.sub.io.

A method and a system automatically perform an image reconstruction of a biological object. The method includes acquiring at different time points t_i signal data for imaging the biological object and clustering a set of data in connection with the acquired signal data. The clustering includes constructing a matrix C, wherein an element C.sub.i,j of the matrix C is the value n_j of one of the data of the dataset acquired at the time point t_i, and then performing a similarity clustering based on the matrix C. At least one of the clusters is selected and determining for each of the time points t_i that are part of the cluster all acquired signal data that have been acquired within a predefined temporal threshold with respect to the considered time point t_i. The image reconstruction of the biological object is performed with the previously determined acquired signal data.

Devices and methods are provided for analyzing images from a magnetic resonance (MR) system. The device includes at least one hardware processor coupled with a storage system accessible to the at least one hardware processor. The device further includes a display in communication with the at least one hardware processor. The device receives a plurality of non-contrast MR images in a region of interest (ROI). The device obtains blood flow signals from the plurality of non-contrast MR images. The device identifies an abnormal segment by analyzing the blood flow signals. The device displays the non-contrast MR images by a highlighted segment in at least one of the non-contrast MR images to indicate the abnormal segment on the display.

A method is for using measurement data of an object of examination for a post-processing process. In an embodiment, the method includes recording first measurement data, the first measurement data being previously determined via a medical imaging modality; automatically analyzing the first measurement data based on defined criteria and automatically inspecting a set of control parameters with aid of an analysis of the first measurement data using defined criteria with regard to second measurement data, the second measurement data being previously recorded via the modality using the set of control parameters, wherein the defined criteria include at least one of a post-processing capacity and identification of at least one image characteristic; and using at least one of the first measurement data and the second measurement data in a post-processing process. A control device and a medical imaging system are also disclosed.

The present invention provides a positioning method for a magnetic resonance imaging system, a magnetic resonance imaging system, and a non-transitory computer-readable storage medium. The positioning method for the magnetic resonance imaging system comprises: acquiring a scattering parameter curve of a body coil during a process in which an examination table carrying a subject under examination enters a scanning bore of the magnetic resonance imaging system; acquiring the position of a part to be examined of the subject under examination on the basis of the scattering parameter curve; and moving the examination table on the basis of the position of the part to be examined such that the part to be examined is located at the center of the scanning bore.