95 results about "T2 weighted" patented technology

The invention discloses a multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system and method. The multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system comprises three portions of an image preprocessing module, a parameter processing module and a prediction and evaluation module. According to the multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system, the characteristics of a T2 weighted image, a diffusion weighted image and a dynamic enhanced image are comprehensively utilized and the purpose of the identification of the prostate cancer focus is achieved through an artificial neural network structure; the ROC (Receiver Operating Characteristic) area under curve of the peripheral zone of prostate of the system is 0.931 and the identification accuracy is 0.887 and the ROC area under curve in the central gland is 0.909 and the identification accuracy is 0.915 through a test; the image information obtained through the conventional magnetic resonance imaging scanning sequence scanning sequence can be well integrated, quantitative parameters in the images are utilized in a maximum mode, and the identification result of the prostate cancer is objectively provided; the operation is simple and convenient, the reference can be intuitively provided for doctors, and the important basis is provided for the subsequent diagnosis scheme.

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.

In a magnetic resonance tomography apparatus and method for determination of T2-weighted images of tissue with short T2 time, in the framework of a steady-state free precession sequence with non-slice-selective RF excitation pulses and projection-reconstruction methods, in each sequence repetition a first steady-state is read out in the form of a half echo and a second steady-state signal is read out in the form of a further half echo with very short echo times TE₁ and TE₂=2TR−TE₁, and are combined by weighted addition such that an MRT image of tissue with very short T2 time is obtained with the sequence.

The invention belongs to the technical field of computer auxiliary diagnosis, and specifically relates to an identification method of primary central nervous system lymphoma and glioblastoma based on a sparse representation system. The method includes: segmenting T1 enhanced and T2 weighted MRI image tumor regions by employing an image segmentation method based on a convolutional neural network; then designing a dictionary learning and sparse representation method, and extracting texture characteristics of the tumor regions; selecting some characteristics with high stability and high resolution for tumor identification by employing an iterative sparse representation characteristic selection method in order to reduce the characteristic redundancy and improve the tumor identification efficiency; and finally establishing a combined sparse representation classification model containing two modals of T1 enhanced or T2 weighted based on the thought of eigenstate fusion in order to improve the tumor identification precision. According to the method, high tumor identification precision can be obtained, manual operation for extraction of identification parameters is avoided, the robustness is high, and the method can be applied to clinic identification of primary central nervous system lymphoma and glioblastoma.

The invention relates to a tumor-targeted T1-T2 double nuclear magnetic resonance imaging contrast agent and a preparation method and an application thereof. The contrast agent comprises hyaluronic acid-coated ferroferric oxide composite magnetic nanoparticles, wherein the molecular formula of hyaluronic acid is as shown in the specification; n is an integer of 17-290. The preparation method of the contrast agent comprises the following steps: (1) dissolving hyaluronic acid into deionized water, introducing a gas, and heating to obtain a reaction system A; (2) dissolving ferric salt and ferrous salt into a strong acid to obtain a solution B; (3) injecting the solution B into the reaction system A, adjusting the pH to be alkaline, and then refluxing at a high temperature to obtain a reaction system C; and (4) cooling a reaction system C to a room temperature, and dialyzing to obtain the contrast agent. The invention further provides an application of the contrast agent in T1 and T2 weighted imaging in in-vivo and in-vitro nuclear magnetic resonance. The contrast agent provided by the invention has superparamagnetism and outstanding T1 and T2 relaxation enhancement effects, and is suitable for being used as a T1-T2 double nuclear magnetic resonance imaging contrast agent.

In a method to control a magnetic resonance system to generate magnetic resonance exposures of an examination subject, a first magnetic resonance radio-frequency pulse with a pulse length of at most 50 μs is initially emitted in a volume region of the examination subject. At least one second magnetic resonance radio-frequency pulse, whose phase is essentially rotated by 180° relative to the first magnetic resonance radio-frequency pulse, with a pulse length of at most 50 μs, is emitted in the same volume region of the examination subject in a predetermined time interval immediately after the first magnetic resonance radio-frequency pulse. An acquisition of raw data from the volume region of the examination subject then takes place. Furthermore, a control device for operating a magnetic resonance system as well as a magnetic resonance system with such a control device to implement such a method, are described.

The invention provides an encephaledema segmentation method and system based on a support vector machine algorithm, which are applied to the medical diagnosis technology field. The encephaledema segmentation method comprises steps of using a plurality of CT images and a plurality of magnetic resonance T2 weighted images of patients suffering from first type hemorrhagic cerebral apoplexy to train a classifier based on the support vector machine algorithm, using the classifier to perform encephaledema segmentation on CT images of patients suffering from the second type hemorrhagic cerebral apoplexy, wherein the patients suffering from the first type hemorrhagic cerebral apoplexy have the CT images and the magnetic resonance T2 weighted images; and the patients suffering from the second type hemorrhagic cerebral apoplexy only have the CT images and do not have the magnetic resonance T2 weighted images. The invention utilizes few patients suffering from the hemorrhagic cerebral apoplexy having the CT images and the magnetic resonance T2 images to perform combined modeling, through studying, establishes a classifier which can identify the encephaledema on the CT from the CT image characteristics, can be applied to the patients who suffer from the hemorrhagic cerebral apoplexy and have the CT images and have no magnetic resonance T2 weighted images, and obtains the higher encephaledema segmentation accuracy.

A cervical caner image automatic partition method based on T2 weighted magnetic resonance imaging (MRI) T2-MRI and dispersion weighted (DW)-MRI includes that a DW-MR image is registered to a T2-MR image by using a non-linear register method, and the registered DW-MR image is sorted; the T2-MR image is filtered through non-linear anisotropic diffusion filtering technology, a bladder and a rectum are partitioned, and an interested area is partitioned through a partition result of the bladder and the rectum; and a combined maximum a posterior (CMAP) method is adopted for an interested area of the T2-MR image and the DW-MR image to conduct precise partition of a tumor. The cervical caner image automatic partition method fully uses effective information of the T2-MR image and the DW-MR image, can effectively overcome effects of noise, partial volume effect and strength overlapping in the T2-MR image, is precise and effective, and has important clinical and application value on prevention, diagnosis and treatment of the cervical cancer.

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 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.

In a first aspect this invention provides methods comprising administering an aqueous contrast agent to the vascular system of a subject, and performing a magnetic resonance scan to detect the MR signal enhancement effects of the aqueous contrast agent. In embodiments the magnetic resonance scan comprises applying at least one pulse sequence selected from a PD-weighted pulse sequence, a T1-weighted pulse sequence, a T2-weighted pulse sequence, and a D-weighted pulse sequence. In embodiments the magnetic resonance scan comprises applying a T1-weighted pulse sequence. A system for performing perfusion MRI comprising an aqueous contrast solution and an injection apparatus configured to provide a maximum injection rate of the aqueous contrast solution to a subject vascular system of at least about 5 ml/s. is also provided.

The invention relates to a method of MR imaging of at least a portion of a body (10) of a patient placed in an examination volume of an MR device (1). The acquisition of high-resolution three-dimensional FLAIR images as well as T2-weighted images at high main magnetic field strength (>3 Tesla) results in unacceptable long scan times. The present invention contemplates a new and improved MR imaging method which overcomes this problem. The method of the invention comprises the steps of subjecting the portion of the body (10) to a first imaging sequence (S1) for acquiring a first signal data set; immediately subsequent to the first imaging sequence (S1) subjecting the portion of the body (10) to an inversion RF pulse that inverses longitudinal magnetization within the portion; after an inversion delay period (TI) subjecting the portion of the body (10) to a second imaging sequence (S2) for acquiring a second signal data set; reconstructing first and second MR images from the first and second signal data sets respectively.

The invention relates to a method for positioning three axial positions of a fetal brain through magnetic resonance. The method is used for further rapidly, accurately and normatively positioning an image of the three axial positions of the fetal brain on the basis of the traditional nuclear magnetic resonance scanning and positioning technology and providing a more accurate and normative cross-section image for clinical medicine. Because the position and the direction of a fetus in a parent are possibly changed at any time, the standard three axial positions of only a few fetuses can be directly positioned through the standard three axial positions of the parent; in many cases, the position of the fetus in the parent is changeable; the standard image of the three axial positions cannot be obtained through the traditional technology; when the standard three axial positions of the parent cannot be given or the standard three axial positions of the fetus cannot be better given, a series of images of various positions can be obtained by rotating and positioning in 360 DEG through a haste sequence, namely a heavy T2 weighted line; and the image closest to the standard fetal position is selected from the series of images and served as the standard to position the brain.

The invention relates to a nuclear magnetic resonance multi-weighted imaging method based on a depth generative adversarial neural network, which comprises the following four steps: the constructionof the depth generative adversarial neural network, the construction of a training data set and an evaluation data set, the training of network weights and the application of the network weights to aplurality of weighted nuclear magnetic resonance imaging. More than 40,000 pairs and 10,000 pairs of T2-weighted and PD-weighted NMR images collected from the same site at the same time were used as training data set and evaluation data set respectively, The model weight of the depth generative adversarial neural network is trained, and the generation network uses the T2-weighted image as the input of the network, and maps the data distribution of the generated image to the PD-weighted image data distribution obtained by acquisition maximally; The invention can convert the T2-weighted nuclearmagnetic resonance image acquired by the nuclear magnetic resonance imaging device into a high-quality PD-weighted nuclear magnetic resonance image in a very short time, thereby providing two kinds of weighted nuclear magnetic resonance images in a single imaging process.

A fast 3D T_2-weighted imaging system and method is disclosed that uses balanced steady state free precession (bSSFP), variable flip angles, and an interleaved multi-shot spiral-out phase encode ordering strategy to acquire high resolution T₂-weighted images quickly while maintaining spatial resolution.

The present invention relates to contrast agent enhanced medical ultrasound imaging. In particular, the contrast agents provided are useful for cell imaging and cell therapy, as well as in vivo targeting, drug delivery and perfusion or vascular imaging applications. More specifically, it provides a particle comprising a fluorinated organic compound and a metal. Such particles may be advantageously employed in qualitative or quantitative imaging such as acoustic imaging including photoacoustic and ultra-sound imaging, MRI imaging, such as 19F imaging, 1H imaging including T1 and T2 weighted imaging, SPECT, PET, scintigraphy, fluorescence imaging and optical coherence imaging and tomographic applications. This may then be employed in cell labeling, microscopy, histology or for imaging vasculature or perfusion in vivo and in vitro.