123 results about "T1 weighted" patented technology

An obturator with an elongated shaft, a proximal end, a substantially closed distal end and a MRI detectable distal shaft portion, which does not interfere with magnetic resonance imaging of tissue proximate thereto. Preferably, the distal shaft portion has an effective MRI detectable mass so as to provide a clear, T1-weighted image within an outline of the distal shaft portion upon magnetic resonance imaging.

A system and method for mimicking a human brain for MR imaging at various magnetic field strengths is disclosed. A phantom is constructed of a structure having a number of sections. A first section contains a mixture of nickel chloride, agarose gel powder, potassium sorbate, deuterium oxide, and water such that the T1, T2, and proton density values of the first section mimic white matter of the human brain. A second section contains different amounts of the same components such that the T1, T2, and proton density values of the second section mimic gray matter of the human brain. As such, when the phantom is scanned in an MR imaging machine, an optimized flip angle for T1-weighted imaging to improve contrast between white matter and gray matter of the human brain that takes into account proton density differences therebetween can be determined.

The invention discloses a synchronous acquisition and calibration method for three-dimensional multi-parameter weighted magnetic resonance imaging. A three-dimensional/two-dimensional fast multi-echo water-fat separation sequence and a signal debugging method, a pre-scanning method, a scanning method, a data preprocessing method and an image reconstruction method thereof can obtain a water-fat separation image and T2 weighted (T1 weighted or PD weighted) image by one-time scanning. The three-dimensional multi-parameter weighted synchronous scanning and calibration method can maximize the number of images obtained in a single scan, including, an in-phase image, a reverse-phase image, a fat image, a fat-pressed image water, a conventional T2 weighted (or T1 weighted/PD weighted ) image, and a T2weighted images, significantly shortens clinical scanning time and increases the selectivity of clinical scanning schemes, and has less reliance on the hardware performance of an MRI system.

A magnetic resonance imaging (MRI) apparatus and a method of processing an MR image are provided. The MRI apparatus includes a scanner configured to acquire a first image that is a T1-weighted image and a second image that is a fluid attenuated inversion recovery (FLAIR) image by performing an MRI scan on a brain. The MRI apparatus further includes an image processor configured to determine a white matter region in the second image based on the first image and the second image, and detect a white matter hyperintensity (WMH) region in the determined white matter region. The MRI apparatus further includes an output interface configured to display the detected WMH region and a change in the WMH region over time.

A method and system for detecting lymph nodes in multiple complementary magnetic resonance (MR) sequences is disclosed. Anatomical landmarks, such as blood vessels, are extracted in a first MR sequence, such as an MR angiography (MRA) image. A search area is defined in at least one second MR sequence, such as a T1 weighted VIBE image, based on the anatomical landmarks extracted the first MR sequence. Lymph nodes are then detected in the search area of the second MR sequence. The lymph nodes can be detected by segmenting the search area into homogenous regions and determining whether each region is a lymph node using feature analysis.

The invention discloses a preparation method of RGD-modified ultra-small magnetic iron oxide nanoparticles. The preparation method comprises the following steps: preparing ultra-small magnetic iron oxide nanoparticles by taking ferric acetylacetonate as a reaction raw material and a precursor, taking oleylamine as a surfactant and a reducing agent and taking dibenzyl ether as a solvent; replacing oleylamine molecules wrapped on the surfaces of the nanoparticles by utilizing dopamine-modified HOOC-PEG-COOH to realize PEG-modification of the surfaces of the nanoparticles; and finally, chemically coupling RGD cyclic peptide by virtue of free carboxyl at the tail end of the PEG to obtain the RGD-modified ultra-small magnetic iron oxide nanoparticles. The method of synthesizing the ultra-small magnetic iron oxide nanoparticles has the characteristics of a simple process, a high raw material conversion ratio, strong repeatability and the like. The synthesized magnetic iron oxide nanoparticles have the characteristics of a regular morphology, an ultra-small dimension, good stability, good monodispersity, high biocompatibility, and tumor specific targeting, and the like, and can be used as a T1-weighted imaging high-performance magnetic resonance imaging contrast agent with a tumor active targeting function.

In a method in the form of a turbo spin echo imaging sequence with long echo trains and optimized T1 contrast for generation of T1-weighted images of an examination subject by magnetic resonance, magnetization in the examination subject is excited with an RF excitation pulse, a number N of RF refocusing pulses with variable flip angle are radiated to generate multiple spin echoes for an excitation pulse, a restoration pulse chain is activated after switching of the N refocusing pulses and before the next RF excitation pulse. The restoration pulse chain influences the magnetization such that the magnetization is aligned opposite to the direction of the basic magnetic field by the restoration pulse chain before the next RF excitation pulse.

A system for processing a medical image for personalized brain disease diagnosis and status determination, includes: an image processing unit, which obtains a 3D T1 weighted image, a 2D T2 fluid attenuated inversion recovery (FLAIR) image, a magnetic resonance angiogram (MRA) image, which images only a vessel for checking abnormality of a brain vessel, and a 4D phase-contrast flow image for recognizing a state of a blood flow in a vessel; a complex image analyzing unit, which selects a disease-to-be-diagnosed, sets a brain area according to the selected disease, and analyzes brain tissue and a brain vessel; and a personalized diagnosis and result output unit, which outputs a brain state, a disease-specific risk degree, a risk of disease, and a disease prediction result through a machine learning algorithm by utilizing an age-specific data DB.

Methods of, and systems for, magnetic resonance imaging of diagnostic mapping of tissues, where sodium mapping is performed individually, as well as in combination with other images of tissue, such as T1ρ, T2, and/or T1-weighted images. In one method embodiment, a sodium image of the tissue is acquired during the same scanning session. Maps are constructed of each of the first and sodium images individually, and in combination, and further facilitate viewing in combination with each other as a single, blended image of the tissue. Maps of the images may be displayed individually or in combination with each other.

The invention provides a method and a device for establishing an age prediction model, an age prediction method and a device. The method comprises: building m references on the x-axis, y-axis, z-axisData sets (described in the description) corresponding to T1-weighted images of brain slices in each slice direction and T<n><n>(z, g), where w refers to the white matter T1-weighted image corresponding to the white matter region and g refers to the grey matter T1-weighted image corresponding to the grey matter region; n is the number of the reference person and n has a value ranging from 1 to m.According to the true age of the reference person corresponding to the T1-weighted image, age identification is added to the T1-weighted image in each data set. Convolution-based neural network pairdata sets (described in the description) and T<n><n>(z, g), corresponding data sets (described in the description)and <n><n>(z, g) are established. The age predictor model with the highest precision of age prediction is selected as the age predictor model.

The invention discloses a brain function network classification method based on a variational autoencoder. The method comprises the following steps: The method comprises the following steps of: acquiring T1 weighted MRI and rs-fMRI of a plurality of normal people and patients with brain cognitive impairment; carrying out pretreatment; carrying out double regression analysis by taking the preprocessed rs-fMRI as a regression dependent variable and the brain function network as a regression independent variable to obtain an individual level brain function network; constructing a deep variationalautoencoder (VAE) model, taking the obtained individual level brain function network diagram as the input and output of the VAE, and taking the encoder part as a feature extraction module for obtaining the implicit code of the individual function network; constructing a multi-layer sensor network to classify the codes obtained by the VAE in the step 4; and deducing samples in the test set by using the trained classifiers for different brain function networks, and fusing deduction results of the classifiers to obtain a final classification result.acquiring T1 weighted magnetic resonance imagesT1 Weighted MRI and resting state functional magnetic resonance images rs-of a plurality of normal persons and patients with brain cognitive impairment; fMRI; carrying out pretreatment; pretreated rs- Performing double regression analysis by taking fMRI as a regression dependent variable and taking the brain function network as a regression independent variable to obtain an individual level brainfunction network; constructing a depth variation auto-encoder (VAE) model, taking the obtained individual level brain function network diagram as input and output of the VAE, and taking the encoder part as a feature extraction module for obtaining hidden codes of the individual function network; constructing a multi-layer perceptron network to classify the codes obtained by the VAE in the step 4;inferring samples in the test set by utilizing a plurality of trained classifiers for different brain function networks, and fusing inference results of the plurality of classifiers to obtain a finalclassification result; according According to the invention, the classification accuracy is improved.

The invention discloses an image analysis method, which comprises the steps of: obtaining a group of T1 weighted images including a control group image and an experimental group image, pre-processing all T1 weighted images, carrying out non-linear registration on preprocessed T1 weighted images into a preset template image, dividing the non-linear registered T1 weighted images to generate a plurality of interest regions, extracting at least one feature data of each interest region to obtain feature matrix information, calculating to obtain a reference value according to a preset Bayesian multi-layer model and the feature matrix information, and judging difference significance of the interest regions between the experimental group image and the control group image according to the relation between the reference value and a preset threshold value. The invention also provides a corresponding image analysis system. The image analysis method and the system can extract more and richer parameters to be analyzed and more diverse information in comparison with the conventional technology, and can simultaneously process multi-region multi-feature significance statistical test so that morphology analysis is more complete.

A system and method for generating simulated post-contrast T1-weighted magnetic resonance (MR) images without the use of exogenous contrast material based upon patient-specific non-contrast MR images using machine learning/artificial intelligence techniques to train the system to generate post-contrast T1-weighted magnetic resonance images based upon retrospectively collected non-contrast MR images of various sequence types including T1-weighted, T2-weighted, FLAIR (Fluid-Attenuated Inversion Recovery), and/or DWI (Diffusion-Weighted Imaging).

The invention relates to a magnetic nanoparticle, and a preparation method and application thereof. Specifically, the magnetic nanoparticle has the characteristics that 1) the magnetic nanoparticle is ferrite; 2) the magnetic nanoparticle has a particle size of 0.1 to 30 nm; 3) the relaxation rate r1 of the magnetic nanoparticle is no less than 1.2 m/M/s; 4) a ratio of a relaxation rate r2 to the relaxation rate r1 of the magnetic nanoparticle is no more than 3.5 and no less than 1.05; and 5) the T1 weighted signal intensity of 0.5mM of the magnetic nanoparticle is no less than 70. The invention also discloses the preparation method and application of the magnetic nanoparticle. When the magnetic nanoparticle is applied to magnetic resonance imaging, a high-quality MRI contrast agent with substantial and excellent imaging performance, high magnetosensitivity and rich T1 signals can be obtained, and the MRI contrast agent is improved in discovery and detection of tumors, cardio-cerebrovascular diseases and other serious diseases, so medical detection and treatment cost can be substantially lowered.

Embodiments of the invention disclose a magnetic resonance imaging method and system. The method comprises the following steps: applying non-layering inverse pulses to a detected object; simultaneously stimulating multiple layers of a heart by using a preset imaging sequence in a set heart movement phase in a first heartbeat period, and acquiring a multilayer aliasing T1 weighted image of the heart; acquiring a reference image by using a preset imaging sequence stimulated by a preset overturning angle in a set heart movement phase in a second heartbeat period, wherein the first heartbeat period and the second heartbeat period correspond to a same breath-holding and are two adjacent heartbeat periods, and the reference image corresponds to one layer of the multiple layers; and performing the interlayer de-aliasing and phase-sensitive reverse restoration re-establishment for the multilayer aliasing T1 weighted image by using the reference image to obtain a target T1 weighted image of each layer of the heart. By virtue of the technical scheme, on the premise of ensuring the image quality, the magnetic resonance data acquisition efficiency can be improved.

The invention discloses albumin nanoparticles realizing co-delivery of an antitumor drug and an MRI (magnetic resonance imaging) contrast medium and a preparation method of the albumin nanoparticles and further provides an albumin nanoparticle vector containing the MRI contrast medium, and drug loading is realized through electrostatic adsorption and coordination between the drug and the vector as well as crosslinking of amino acid residues of the vector. The invention further discloses an optimal preparation technology of the albumin nanoparticles realizing co-delivery of the antitumor drug and the MRI contrast medium and a function of the albumin nanoparticles in diagnosis and treatment combination of tumors. According to the albumin nanoparticles realizing co-delivery of the antitumor drug and the MRI contrast medium, the drug uptake ratio of cells can be increased, and drug efflux caused by drug-resistant cells is reduced, so that drug resistance is reversed, and efficient delivery of the drug is realized; the albumin nanoparticles realizing co-delivery of the antitumor drug and the MRI contrast medium have excellent T1 weighted imaging capability and an effective means is provided for the diagnosis and treatment combination of the tumors.

The invention discloses a method and system for automatically extracting the extracting magnetic resonance image corpus callosum. The method comprises the steps of according to a midsagittal plane T1 weighted nuclear magnetism brain image, determining a brain outline threshold value and a corpus callosum threshold value; performing threshold segmentation on the image according to the brain outline threshold value and the corpus callosum threshold value to respectively obtain a brain outline binary image and a corpus callosum binary image; respectively performing margin tracing on the brain outline binary image and the corpus callosum binary image to acquire a brain outline position and a corpus callosum margin cluster; establishing a decision tree, and screening marginal information to determine a corpus callosum region; determining an angle of inclination and a central position of a brain scanning line set according to the corpus callosum region. By means of the method and system, the corpus callosum in the midsagittal plane T1 weighted nuclear magnetism brain image can be extracted automatically, automatic regulation of the scanning line set during brain scanning can be completed according to information on the corpus callosum and the like, scanning efficiency is increased, no manual regulation is needed, time and labor are saved, an strong practicability is achieved.

The invention discloses a double-functional nano-composite spheres based on metal ion-inducing polypeptide self-assembly and a preparation method thereof. In the invention, by means of a one-step reaction synthesis method, with [alpha]-lactalbumin hydrolyzed polypeptide as a carrier, the nano spheres are self-assembled under induction by Ca<2+> and Gd<3+> together, wherein the nano spheres, during self-assembly, are wrapped by a photosensitive agent, rose Bengal. The particle size of the nano-composite spheres can be adjusted and controlled in the range of 100-500 nm. The Gd<3+> which participates in the inductive sphere forming is used as a contrast medium unit of magnetic resonance imaging and the T1-weighted nuclear magnetic resonance signal response can be effectively increased so that the magnetic resonance imaging diagnosis to a tumor site can be performed. The rose Bengal wrapping the nano-composite spheres can release singlet oxygen to kill tumor cells under excitation illumination at 550 nm, thereby achieving the effect of photodynamic treatment. The nano-composite spheres are toxic-free without illumination. Meanwhile, the treatment process allows tracing through the magnetic resonance imaging. In addition, the nano-composite spheres are low in preparation cost, are simple in processes, and have a potential wide application prospect in the bio-medicinal field.

The invention relates to the field of synthesis of nanomaterials, in particular to a method for synthesizing silk fibroin nanoparticles and a method for rapidly and gently encapsulating manganese dioxide onto the surfaces of silk fibroin nanoparticles inspired by biomineralization. The method specifically includes the following steps: (1) silk fibroin extraction and silkworm cocoon degumming; (2)self-assembly of the silk fibroin nanoparticles in an acetone solution; (3) utilizing silk fibroin balls as both a template and a reducing agent to react with a potassium permanganate solution to produce manganese dioxide in situ on the surfaces of the silk fibroin nanoparticles. A resulting multifunctional nano platform has photothermal performances, drug delivery capabilities, catalytic activitysimilar to catalase and T1-weighted nuclear magnetic resonance imaging capabilities. The preparation has great potential for application in the fields of biomedicine and other areas of social economy.

The invention discloses a high-grade serous ovarian cancer recurrence risk prediction system based on imaging omics. A method comprises the steps of T1 weighted enhanced imaging omics processing, T2 weighted imaging omics processing and information fusion. The image omics processing mainly comprises the steps of three-dimensional tumor segmentation, image standardization, image omics feature extraction, feature normalization, feature screening, SMOTE resampling and classifier training; the information fusion is mainly used for fusing recurrence risk prediction probabilities output by T1 and T2image omics processing, so the risk prediction accuracy is further improved.