25 results about "Inversion recovery" patented technology

The invention relates to the technical field of medical image auxiliary diagnosis, in particular to a nuclear magnetic resonance image auxiliary diagnosis method and system based on multi-modal fusion. The method comprises the following steps: step 1, synchronously acquiring a three-dimensional T1 weighted structure image, a T2 weighted fluid attenuation inversion recovery image and diffusion weighted imaging data of a subject, carrying out spatial registration by taking the T1 weighted image as a reference, and executing skull stripping and gray scale standardization; 2, individualized brain region segmentation is carried out based on a brain anatomical map, the lesion sensitivity weight of each modal is calculated for each segmented brain region, and the weight is obtained by quantifying the following parameters; step 3, extracting multi-modal image features in each brain region; and 4, inputting the fusion features of the whole brain region into a multi-task classifier. The standardization and alignment of the multi-mode MRI image in the space and gray level are realized, and the problems of space mismatch and feature interference among different modes are effectively solved.

The invention relates to a special device and method for calibrating a relaxation time measurement result of a medical magnetic resonance imaging (MRI) system. The special device comprises a relaxation time standard die body, an optical fiber temperature measurement system and a control computer. The relaxation time standard die body is composed of a die body shell, a sealing cover and a relaxation time standard unit. The relaxation time standard unit is composed of reagent bottles, and the optical fiber temperature measuring probe is inserted into the relaxation time standard die body. According to the method, T1 and T2 standard values of a relaxation time standard substance under different static magnetic field intensities are calibrated by using a magnetic resonance spectroscopy method, and a relaxation time measurement result of an MRI system is calibrated by using the calibrated relaxation time standard substance. And adopting a reversal recovery sequence to calibrate T1, and adopting a CPMG sequence to calibrate T2. The device and the method can be used for calibrating the relaxation time measurement result of the MRI system, so that the accuracy and the consistency can be improved, and the clinical application is promoted.

The application relates to a magnetic resonance imaging method, device, computer equipment, storage medium and computer program product. The method comprises the following steps: in a first cardiac cycle, a characteristic electrocardio signal of a detection object is identified, a first sequence pulse is applied to the detection object after a preset delay time of identifying the characteristic electrocardio signal, and the first sequence pulse is used for reversing a longitudinal magnetization vector of the detection object; after the first sequence pulse is applied, a second sequence pulse of a target phase mode is applied to the detection object after a recovery time, and an initial cardiac imaging set is acquired, wherein the target phase mode is one of at least two different phase modes, and different target phase modes correspond to different positions of artifacts in the initial cardiac imaging sets; and the initial cardiac imaging sets obtained in each first cardiac cycle are subjected to first registration processing to obtain a cardiac imaging. The method can effectively weaken the artifacts in cardiac delayed enhancement imaging, and does not increase additional operations and additional scanning time.

A low field magnetic resonance imaging (MRI) stroke identification sequence uses an inversion recovery sequence. TE is set to the minimum or near-minimum value achievable by a system to minimize an impact of T2 effect on a signal S. Additionally, it selects combinations of TR values and corresponding TI values to make signal from cerebral hemorrhage appear as high signal, and signals from cerebral infarct tissue and cerebral parenchyma appear as isointense or low signal. This allows for rapid and accurate determination of hemorrhagic stroke and, by utilizing low-field magnetic resonance, enhances the accessibility for patients.

The invention discloses intelligent diagnosis equipment for brain small vasculopathy MRI image enhancement, which comprises a multi-mode MRI image acquisition module, an examination bed is arranged on one side of the multi-mode MRI image acquisition module, the multi-mode MRI image acquisition module is used for acquiring multi-sequence MRI original images of a patient with brain small vasculopathy, and the multi-sequence MRI original images at least comprise T1 weighted imaging T1WI, T2 weighted imaging T2WI and liquid attenuation inversion recovery sequence FLAIR images; the invention belongs to the technical field of medical equipment, and aims at solving the problems that in the prior art, a traditional MRI image is limited in resolution and is interfered by noise and artifacts, the signal difference between a focus and normal brain tissue is not obvious, and missed diagnosis is prone to occurring. The method has the advantages that the space-channel attention mechanism of the intelligent image enhancement module is fused with the multi-modal features, the signal difference between the tiny focus and the normal brain tissue is remarkably enhanced, noise and artifact interference are weakened, the detection rate of the tiny focus is greatly increased, and the missed diagnosis risk is effectively reduced.

The invention relates to a magnetic resonance image reconstruction method and device, computer equipment and a storage medium, and the method comprises the steps: applying a phase-sensitive inversion recovery pulse sequence to a to-be-imaged object, collecting a magnetic resonance signal of the to-be-imaged object, and obtaining a to-be-processed image according to the magnetic resonance signal; removing a background first-order phase in the to-be-processed image to obtain a first dephasing image; according to the first dephasing image and a preset recognition model, removing a target background zero-order phase in the first dephasing image to obtain a second dephasing image; and extracting a real part component of the second dephasing image to obtain a target magnetic resonance image. By using the magnetic resonance image reconstruction method provided by the invention, the quality of the obtained target magnetic resonance image can be improved.

The invention provides an imaging signal acquisition method and system of multiple acquisition modules based on inversion recovery pulses, electronic equipment, a storage medium and a computer program product. The imaging signal acquisition method comprises the steps that an inversion recovery pulse is applied to a first layer of a target space position at a first moment, so that at least two acquisition modules sequentially acquire imaging signals of the first layer after first inversion recovery time, and the first inversion recovery time is the inversion recovery time of the first acquisition module; under the condition that the first inversion recovery time meets a first preset condition and the interval time between two adjacent acquisition modules does not meet a second preset condition, determining a first target layer number meeting the execution of interlayer staggered acquisition; and applying inversion recovery pulses to the layers of the first target layer number in sequence within the first inversion recovery time, so that the at least two acquisition modules acquire imaging signals of the corresponding layers in sequence after the first inversion recovery time.

The present disclosure may include a communication module configured to perform communication with an imaging device that captures an image of an acute cerebral infarction patient; and a processor configured to receive the image of the acute cerebral infarction patient from the imaging device through the communication module, classify the image into a first image corresponding to a liquid attenuation inversion recovery image and a second image corresponding to a diffusion-weighted image, acquire the first image and the second image, align the first image and the second image with respect to an MNI region corresponding to an activated region of a brain, detect an infarction region in the second image, and output a probability prediction value for the occurrence time of acute cerebral infarction based on the first image, the second image, and the infarction region.

A magnetic resonance imaging method and a magnetic resonance imaging system is provided. The method is used to acquire, in a plurality of consecutive time units, magnetic resonance signals representing one or more layers of an anatomical region of interest of a subject and generate a magnetic resonance image. The method includes: determining an effective repetition time of an (N−1)th time unit; determining the position of an inversion recovery pulse in an Nth time unit based on the effective repetition time of the (N−1)th time unit, wherein N is an integer greater than 1; transmitting, in the Nth time unit, a scan sequence generated based on the position of the inversion recovery pulse, and acquiring a magnetic resonance signal representing an anatomical region of interest of a subject; and reconstructing a magnetic resonance image at least based on the magnetic resonance signal.

The invention discloses a brain multi-modal image data processing method and device. The method comprises the steps of obtaining a brain multi-modal image sequence of a target object; fusing the three-dimensional contrast-agent-free angiography with the plaque internal hemorrhage image sequence and the time leap method imaging image sequence to obtain cerebrovascular image data; cerebrovascular image data is used as a tree root node and a trunk node, hemodynamic parameter data in a phase contrast angiography sequence is used as a branch node for representing a blood supply state, and neural structure parameter data in a diffusion magnetic resonance imaging sequence is used as a branch node for representing a neural structure. Physical and chemical parameter data in the liquid attenuation inversion recovery sequence are used as leaf nodes for representing functional metabolism, hemodynamic parameter data in the magnetic resonance brain perfusion imaging sequence are refined to a pixel level and then are used as leaf nodes for representing metabolic activity, and a brain biological characteristic tree of the target object is constructed. According to the method, the brain multi-modal image data can be quantitatively analyzed.

Disclosed is a method of characterizing a cardiac lesion using an image comprising: a black blood image generated from signals acquired during black blood late gadolinium enhanced magnetic resonance acquisition (ACQ1); a bright blood image is generated from signals acquired during bright blood late gadolinium enhanced magnetic resonance acquisition, the bright blood acquisition step (ACQ2) being different from the inversion recovery sequence. The method comprises: computer segmenting the bright blood image to generate localization data defining a set of at least one wall of the cardiac muscle; the computer extracts the set of at least one wall characterizing a cardiac lesion from the set of at least one wall defining the myocardium from the positioning data of the set of at least one wall according to the black blood image and the positioning data.

The application provides a kind of magnetic resonance image feature extraction method, system, equipment and feature application method, it is related to image feature extraction technical field, the application includes obtaining the magnetic resonance imaging data of sample to be measured;According to magnetic resonance T1 weighted image, magnetic resonance imaging liquid attenuation inversion recovery sequence image and diffusion magnetic resonance image, construct the structure broken link network of sample to be measured;According to resting state functional magnetic resonance imaging, construct the functional broken link network of sample to be measured;According to structure broken link network and functional broken link network, construct individual injury degree network;The one-dimensional vector obtained by converting the upper triangular value on the matrix of individual injury degree network is used as the feature extraction result of the magnetic resonance image of sample to be measured.The application can accurately and reasonably extract the characteristics of magnetic resonance image by constructing structure broken link network and functional broken link network, to improve the precision of model classification.

This application relates to the technical field of image recognition, and provides a method for evaluating a diffusion weighted imaging (DWI)-fluid attenuated inversion recovery (FLAIR) mismatch, an apparatus, a medium, and a product. The method includes: obtaining a DWI image and a FLAIR image of a target object; applying a first image segmentation model to segment the DWI image to obtain a first image segmentation result; applying a second image segmentation model to segment the FLAIR image to obtain a second image segmentation result; registering the second image segmentation result onto the first image segmentation result to obtain a registered second image segmentation result; and applying a Dice metric to evaluate a degree of mismatch between the first image segmentation result and the registered second image segmentation result. This application can improve efficiency of determining whether DWI and FLAIR are matched.

The invention discloses a cerebral apoplexy hemorrhage and ischemia identification scoring method and device based on a low-field-intensity nuclear magnetic imaging, and relates to the technical field of clinical medicines.The method comprises the steps that a 0.23-T diffusion weighted imaging image and a 0.23-T hematoma enhancement inversion recovery sequence image of a patient are obtained; inputting a 0.23-T diffusion weighted imaging image and a 0.23-T hematoma enhancement inversion recovery sequence image of the patient into the trained integrated model of stroke focus segmentation and hemorrhagic and ischemic stroke identification scoring; predicting a focus segmentation mask in a 0.23-T diffusion weighted imaging image of the patient, a focus segmentation mask in a 0.23-T hematoma enhancement inversion recovery sequence image, and probability scores of hemorrhagic and ischemic stroke of the patient; the integrated model is used for predicting a focus segmentation mask in a 0.23-T diffusion weighted imaging image, a focus segmentation mask in a 0.23-T hematoma enhancement inversion recovery sequence image, and probability scores of hemorrhagic and ischemic stroke. The accuracy of stroke risk identification can be improved.

The present invention relates to a stroke differentiation sequence using low-field magnetic resonance imaging, and a device with the differentiation sequence. An inversion recovery sequence is used, and a TE uses the minimum or near-minimum TE value achievable by a system, thereby minimizing the impact of T2 effect on a signal S; moreover, a combination of a TR value and a corresponding TI value is selected, such that the signal of intracerebral hemorrhage is hyperintense, and the signals of cerebral infarct tissue and brain parenchyma are isointense or hypointense, thereby quickly and accurately identifying hemorrhagic stroke; and low-field magnetic resonance imaging is used, thereby achieving higher accessibility for patients.

The application discloses an optimization method, device, equipment and medium for magnetic resonance imaging, and relates to the field of magnetic resonance imaging. The method comprises the following steps: acquiring a reference longitudinal relaxation time of an imaging magnetic resonance device with a preset main magnetic field strength; constructing a linkage fitting function between TR and TI parameters based on the reference longitudinal relaxation time, taking the maximum difference value between an image signal of a hemorrhagic focus and an image signal of healthy brain parenchyma as a target; determining a target TI according to a target TR and the linkage fitting function; optimizing scanning parameters of the magnetic resonance device by using a minimum effective echo time, the target TR and the target TI; acquiring an initial magnetic resonance image, which is obtained by scanning a stroke patient by using the magnetic resonance device with the optimized parameters; and enhancing the initial magnetic resonance image by using a nonlinear stretching function to obtain a stroke triage enhanced inversion recovery image. The application can improve the image contrast of the magnetic resonance imaging.

This invention relates to the field of intelligent medical image analysis technology, and in particular to a deep learning-based method and system for stroke image segmentation. The method includes: acquiring diffusion-weighted, apparent diffusion coefficient, and fluid attenuation inversion recovery images to form a dataset; obtaining standardized images and quality grades through resampling and intensity normalization; training a prior model with normal samples to generate a potential distribution centroid library and quality calibration curve; alternately updating the deformation field and anomaly editing field of the images to be segmented to generate candidate probability maps; zeroing the anomaly editing field to generate counterfactual healthy images; and combining differential evidence and contralateral mirror evidence to output lesion masks and suspicious region masks, thereby improving cross-quality stability and verifiability.

A method of analysing MRI images is described. The method comprising acquiring at least three medical MR images of a subject; analysing the at least three medical MR images to determine a water T1 map; applying a field strength correction and an iron correction to the determined water T1 map to generate a corrected water T1 map; generating one or more simulated MRI images based on the water T1 map; fitting the one or more simulated MR images to determine a standard cT1 image for the subject.

The invention relates to a magnetic resonance imaging method and a magnetic resonance imaging system, and the method comprises the steps: obtaining an initial inversion recovery scanning sequence which comprises an inversion module and an imaging collection module; obtaining first gradient coding position information of a set tissue of the target scanning part according to an imaging acquisition module; according to the first gradient coding position information, gradient coding parameters of an inversion module are determined, and a target inversion recovery scanning sequence is obtained; and scanning the target scanning part according to the target inversion recovery scanning sequence to obtain a magnetic resonance image. By adopting the method, the problem that a fat inhibition method cannot have a relatively good inhibition effect in various occasions can be solved.

The application relates to a magnetic resonance image generation method and device, computer equipment and a storage medium. The method comprises the following steps: in a target cardiac cycle, a preparation module is applied in response to receiving an electrocardio trigger signal to flip a first initial longitudinal magnetization vector corresponding to a detection object into a first transverse magnetization vector and to scatter into a first vector value; an inversion recovery pulse is applied in response to reaching a vector recovery time after the preparation module is applied; magnetic resonance data of the detection object is acquired by using a target imaging sequence in response to reaching an inversion recovery time after the inversion recovery pulse is applied; and the magnetic resonance data is reconstructed to obtain a target magnetic resonance image of the detection object. The method ensures that the longitudinal magnetization vector corresponding to the detection object is recovered from the first vector value to the signal strength of the vector recovery time before the inversion recovery pulse is applied at the interval vector recovery time, so that the longitudinal magnetization vectors corresponding to the detection object are all the same, and the quality of the magnetic resonance image is improved.

The invention discloses a senile dementia related multi-contrast brain structure magnetic resonance imaging analysis method which comprises the following steps: acquiring multi-contrast brain structure magnetic resonance imaging data including T1 weighted imaging, T2 weighted imaging, proton density weighted imaging PD, liquid attenuation inversion recovery FLAIR and magnetic sensitivity weighted imaging SWI; constructing a model for multi-contrast brain structure magnetic resonance imaging analysis, wherein the model comprises an image denoising module, an image registration module and an image segmentation module; inputting the acquired magnetic resonance imaging data into the trained model; in the first step, noise suppression images corresponding to all contrast ratios are output, in the second step, multi-modal image registration is carried out, contrast ratio alignment images of unified voxel grids are generated, and in the third step, a final segmentation probability graph and a corresponding tissue label are output. By using the system and the method, high-quality, automatic and clinically deployable nuclear magnetic resonance imaging (MRI) brain image analysis is realized. The method can be widely applied to the field of medical image processing.

This application provides a magnetic resonance T1 mapping system and method, the system comprising: at least one storage device storing a set of instructions; and at least one processor communicating with the at least one storage device, characterized in that, when the instructions are executed, the at least one processor is configured to cause the system to perform the following operations: acquiring at least three images of a target during an inversion recovery process, each of the at least three images being acquired during breath-holding within a cardiac cycle of the target; and determining a T1 mapping image of the target based on the at least three images acquired during the inversion recovery process and a trained model.

The embodiment of the invention provides a magnetic resonance imaging method and a magnetic resonance imaging system, the method is used for acquiring magnetic resonance signals representing one or more layers of an anatomical region of interest of a subject in a plurality of continuous time units and generating magnetic resonance images, and the method comprises the following steps: determining the effective repetition time of the (N-1) th time unit; determining the position of an inversion recovery pulse in the Nth time unit according to the effective repetition time of the (N-1) th time unit; wherein N is an integer greater than 1; emitting a scanning sequence generated according to the position of the inversion recovery pulse in the Nth time unit, and acquiring a magnetic resonance signal representing an interested anatomical region of the subject; and reconstructing a magnetic resonance image at least according to the magnetic resonance signal.

The invention relates to a transformer oil relaxation self-adaptive detection method and system based on nuclear magnetic resonance, and the method comprises the steps: carrying out the optimization measurement process of transverse relaxation time T2: carrying out the measurement of the transverse relaxation time T2 through employing a CPMG pulse sequence based on a low-field nuclear magnetic resonance system, and collecting a CPMG echo signal in the T2 measurement process; performing Laplace inversion to obtain transverse relaxation time T2 distribution and a maximum T2 component of the transformer oil, and optimizing the number of echoes on the basis of the maximum T2 component; and an optimized measurement process of longitudinal relaxation time T1: based on a low-field nuclear magnetic resonance system, carrying out longitudinal relaxation time T1 measurement by adopting an inversion recovery sequence, carrying out Laplace inversion on multiple groups of collected inversion recovery signals to obtain a maximum T1 component, determining optimal waiting time by taking the maximum T1 component as a reference value, and finally determining an optimal pulse sequence parameter. Compared with the prior art, the method has the advantages of improving the detection precision and efficiency and the like.

The invention relates to a longitudinal relaxation time constant acquisition method and device and a magnetic resonance imaging system. The method comprises the following steps: acquiring a plurality of amplitude images corresponding to a plurality of inversion recovery moments; adjusting the plurality of amplitude images according to a first deviation value of the amplitude in each amplitude image; and obtaining a longitudinal relaxation time constant of a target position point in the amplitude image according to the multiple adjusted amplitude images and the corresponding inversion recovery moments. By adopting the method, the problem of low accuracy of a longitudinal relaxation time constant fitting result can be solved.