73 results about "Black blood" patented technology

To produce a black body angiographic image representation of a subject (42), an imaging scanner (10) acquires imaging data that includes black blood vascular contrast. A reconstruction processor (38) reconstructs a gray scale image representation (100) from the imaging data. A post-acquisition processor (46) transforms (130) the image representation (100) into a pre-processed image representation (132). The processor (46) assigns (134) each image element into one of a plurality of classes including a black class corresponding to imaged vascular structures, bone, and air, and a gray class corresponding to other non-vascular tissues. The processor (46) averages (320) intensities of the image elements of the gray class to obtain a mean gray intensity value (322), and replaces (328) the values of image elements comprising non-vascular structures of the black class with the mean gray intensity value.

DIR imaging of blood vessels by administering a series of DIR preparation pulse modules at a repetition interval short enough that at least two DIR preparation pulse modules generally occur within each RR interval, and by acquiring image data for a plurality of slices following each DIR module.

A multi-slice double inversion recovery (DIR) pulse sequence with read out of a signal for imaging successive slices implemented on a magnetic resonance image scanner. In the method, when the DIR pulse sequence is applied before imaging each slice, a slab-selective inversion re-inverts the entire slab that includes all of the slices. All slices are imaged within a predefined repetition time (TR). The number, N, of slices acquired per TR controls the inversion time to execute the read out of the signal for imaging each slice at a zero-crossing point of blood. In a test, multi-slice DIR images of carotid arteries were obtained with N ranging from 2-8, for four subjects. The results were compared with those for both standard single-slice DIR, and inflow saturation techniques. Multi-slice DIR with N=2-6 provided blood flow suppression in carotid arteries similar to that of single-slice DIR, and significantly better than inflow saturation.

In the black blood method using a double inversion pulse, images in the systole of the cardiac cycle can be captured in a reliable manner even in the presence of a cycle-to-cycle variance in the heart beat cycle. A pulse sequence of the black blood method composed of a double inversion pulse DIV and an imaging pulse train SEQ_ima is used. This sequence is applied in sync with an ECG signal of a subject to be imaged, and magnetic resonance imaging is thereby performed. The double inversion DIV is applied in sync with an R-wave:R1 appearing on the ECG signal at a given timing, with a first delay time td1 (fixed value), and the imaging pulse train SEQ_ima is applied in sync with the following R-wave:R2 with a second delay time td2 (fixed value: set in accordance with the systole). A variance of the cardiac cycle is absorbed in an inversion time BBTI.

The invention discloses a speed selection radiofrequency pulse-based magnetic resonance black blood imaging method, comprising the following steps of designing a speed selection radiofrequency pulse; according to the speed selection radiofrequency pulse, coding a blood flow speed to inhibit a blood flow magnetic resonance signal in a preset speed range; performing black blood imaging after the blood flow magnetic resonance signal is inhibited. According to the black blood imaging method provided by the embodiment of the invention, the blood flow speed is coded by designing the speed selection radiofrequency pulse and according to the speed selection radiofrequency pulse, so the blood flow magnetic resonance signal in the specific speed range is inhibited, the black blood imaging is realized, the blood flow magnetic resonance signal is effectively inhibited, the imaging quality is improved, and the magnetic resonance signal of a static tissue is prevented from being influenced by the blood flow inhibition radiofrequency pulse. The invention also discloses a speed selection radiofrequency pulse-based magnetic resonance black blood imaging system.

The invention relates to a blood vessel center line determination method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a black blood medical image and a bright blood medical image; performing blood vessel identification processing on the black blood medical image and the bright blood medical image to obtain a black blood vessel identification image and a bright blood vessel identification image, and performing registration and fusion processing on the black blood vessel identification image and the bright blood vessel identification image to obtain a fused blood vessel identification image; and extracting the segment center line of each segment of blood vessel in the fused blood vessel identification image, and determining the center line of the blood vessel in the black blood medical image or the bright blood medical image according to the segment center line of each segment of blood vessel. The blood vessel center line determination method provided by the invention can improve the accuracy of extracting the blood vessel center line.

The invention discloses a fast curved surface reconstruction method for a multi-modal multi-contrast medical image and a storage medium. The method comprises the following steps: importing a multi-modal multi-contrast image; selecting two adjacent points as initial seed points for the target blood vessel segment in the image; performing automatic center line search; in the searching process, taking the first initial seed point as a starting point, controlling the searching direction through the second initial seed point, and conducting point-by-point searching on the center line of the target blood vessel segment; smoothening the center line; scanning the smoothed center line along a user-defined direction to obtain an original curved surface required by curved surface reconstruction; and unfolding the original curved surface to obtain a curved surface reconstruction result. According to the method, the center lines of multiple contrast images such as a CT blood vessel image, an MRI bright blood image and an MRI black blood image can be rapidly extracted. In addition, according to the method, a new data structure is adopted to display a two-dimensional plane image, and resampling distortion of a curved surface image is avoided.

A black blood magnetic resonance imaging sequence is performed using a magnetic resonance scanner. The sequence includes: applying a first flow sensitization gradient; applying a spoiler gradient after applying the first flow sensitization gradient; applying a second flow sensitization gradient after applying the spoiler gradient wherein the second flow sensitization gradient has area equal to the first flow sensitization gradient but of opposite polarity; applying a slice-selective radio frequency excitation pulse after applying the spoiler gradient; and performing a magnetic resonance readout after applying the second flow sensitization gradient and after applying the slice selective radio frequency excitation. The readout acquires magnetic resonance imaging data having blood signal suppression in the region excited by the slice-selective radio frequency excitation pulse. The magnetic resonance imaging data is suitably reconstructed to generate a black blood image that may be displayed.

The invention discloses a method for quickly establishing an intracranial blood vessel simulation three-dimensional model based on transfer learning. The method comprises the following steps: collecting a bright blood image group and an enhanced black blood image group of an intracranial blood vessel part; preprocessing each bright blood image and the corresponding enhanced black blood image to obtain a first bright blood image and a first black blood image; performing image registration on the first bright blood image by using mutual information based on Gaussian distribution sampling and a registration method of an image pyramid; utilizing a maximum intensity projection method to obtain MIP images in all directions from the registered bright blood image groups; taking the MIP image as atarget domain, taking the fundus blood vessel image as a source domain, and obtaining a two-dimensional blood vessel segmentation image by using a transfer learning method; performing back projectionsynthesis on the two-dimensional blood vessel segmentation images in the three directions to obtain first three-dimensional blood vessel body data; and obtaining an intracranial blood vessel simulation three-dimensional model by utilizing the second three-dimensional blood vessel body data corresponding to the registered bright blood image group. According to the method, the whole state of the intracranial blood vessel can be simply, conveniently, quickly and visually obtained clinically.

The invention discloses an intracranial blood vessel image fusion method. The method comprises the following steps: acquiring a bright blood image and a black blood image of an intracranial blood vessel; taking the black blood image as a reference image and the bright blood image as a floating image, performing coordinate transformation on the bright blood image, and performing interpolation processing on the bright blood image by adopting a nearest neighbor interpolation method; calculating the similarity between the bright blood image and the black blood image after interpolation processingby using similarity measurement; finding the optimal similarity measurement by using a search strategy, and stopping iteration when the similarity measurement is optimal; according to the space transformation matrix, carrying out coordinate transformation on the bright blood image when similarity measurement is optimal, and obtaining a first registration image; extracting the same scanning area inthe black blood image according to the scanning area of the bright blood image in the first registration image to obtain a second registration image; and adopting a PCA analysis image fusion algorithm to perform image fusion on the two images in the second registration image. According to the scheme, a doctor can be assisted in accurate intracranial disease diagnosis.

A contrast enhancement (CE) agent is infused into blood flowing through a site that is to be imaged with magnetic resonance imaging (MRI). Two double inversion procedures are carried out, forming a quadruple inversion recovery (QIR) pulse sequence. Each double inversion procedure comprises a non-selective and slice-selective inversion RF pulse. The first double inversion procedure is followed by a first predefined inversion delay period, TI₁, and the second procedure by a second predefined inversion delay period, TI₂. A black-blood image can thus be produced in which blood appears consistently black and tissues surrounding the blood, such as a vessel wall, heart, atherosclerotic plaque, or thrombus, are clearly visible. Unlike the prior art black-blood imaging technique, the QIR method does not require a precise knowledge of the T₁ of the blood carrying the CE agent in order to suppress the signal and artifacts caused by the blood flowing through the site.

The invention discloses a magnetic resonance blood vessel wall image analysis method. The method comprises the steps: reading a 3D image; acquiring a bright blood sequence of the 3D image, and automatically extracting blood vessels based on a central line of the bright blood sequence; acquiring a black blood sequence of the 3D image, and registering the center line of the bright blood sequence tothe black blood sequence; reconstructing a whole blood vessel according to the center line of the black blood sequence; obtaining a reconstructed 2D cross section; building a new training model, and training the training model according to the reconstructed lumen and wall characteristics of the 2D cross section; and importing a given blood vessel wall image into the trained training model to predict a lumen and a vessel wall. The invention further discloses a magnetic resonance blood vessel wall image analysis system and a computer readable medium. The blood vessel is reconstructed by matchingthe center line of the bright blood sequence of the 3D image with the black blood sequence, then the characteristics of the lumen and the wall of the tube are automatically obtained through deep learning and learning of a large number of samples, the method does not need to seriously depend on experience of doctors any more, and the segmentation result can be efficiently and accurately obtained.

The invention relates to a blood vessel wall image segmentation method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an intracranial blood vessel wall image of three-dimensional black blood T1 weighted magnetic resonance; performing lumen segmentation on the intracranial vascular wall image to obtain a three-dimensional vascular lumen segmentation result; extracting a center line according to the three-dimensional blood vessel cavity segmentation result, and carrying out re-cutting perpendicular to the center line to obtain a two-dimensional blood vessel wall cross section image; and segmenting the two-dimensional blood vessel wall cross section image to obtain a blood vessel cavity area and an outer tube wall area. The three-dimensional lumen in the magnetic resonance image is firstly segmented, then the two-dimensional lumen is segmented on the two-dimensional blood vessel wall cross section image according to the three-dimensional lumen segmentation result, and the accuracy and the segmentation efficiency of blood vessel wall image segmentation are improved through accurate segmentation of the lumen and the lumen.

The invention discloses an intracranial blood vessel comprehensive image generation method, which comprises the steps of obtaining a plurality of image pairs to be registered of intracranial blood vessels, and preprocessing a bright blood image and an enhanced black blood image in each image pair to obtain a first bright blood image and a first black blood image of the image pair; selecting a partof preprocessed image pairs as test image pairs; performing image registration on the first bright blood image and the first black blood image in each test image pair by adopting a registration method based on mutual information and an image pyramid to obtain a rotation matrix corresponding to the first bright blood image in the test image pair after registration; obtaining the mean value of therotation matrixes of all the test image pairs; utilizing the mean value of the rotation matrix to perform coordinate transformation on the first bright blood images in other preprocessed image pairs except the test image pair, and finishing image registration to obtain a plurality of registered image pairs; and fusing the two images in the registered image pair to obtain an intracranial vessel comprehensive image.

The invention discloses a method for establishing an intracranial vessel simulation three-dimensional stenosis model based on transfer learning. The method comprises the following steps: acquiring a bright blood image group and an enhanced black blood image group of an intracranial vessel; performing image registration by using a registration method based on mutual information and an image pyramidto obtain a registered bright blood image group; utilizing the registered bright blood image group to obtain an MIP image in each direction; obtaining a two-dimensional blood vessel segmentation image based on the MIP image as a target domain and a fundus blood vessel image; synthesizing the two-dimensional blood vessel segmentation images in the three directions by using a back projection methodto obtain first three-dimensional blood vessel body data; obtaining an intracranial blood vessel simulation three-dimensional model by utilizing the second three-dimensional blood vessel body data corresponding to the registered bright blood image group; and for each section of blood vessel in the model, obtaining a numerical value of a target parameter representing the stenosis degree of the section of blood vessel, and marking the intracranial blood vessel simulation three-dimensional model by utilizing the numerical value of the target parameter to obtain a simulated three-dimensional intracranial vessel stenosis analysis model.

The invention discloses a method for establishing an enhanced three-dimensional model for intracranial angiography. The method comprises the following steps: acquiring a bright blood image group, a black blood image group and an enhanced black blood image group of an intracranial blood vessel part; preprocessing each image pair to obtain a first bright blood image and a first black blood image; for each first bright blood image, taking the corresponding first black blood image as a reference, and performing image registration by using mutual information based on Gaussian distribution sampling and a registration method of an image pyramid to obtain a registered bright blood image group; carrying out flow empty artifact elimination operation to obtain an artifact elimination enhanced black blood image group; subtracting corresponding images in the artifact elimination enhanced black blood image group and the black blood image group to obtain K contrast enhanced images; establishing a blood three-dimensional model and a blood vessel three-dimensional model of blood boundary expansion by using the registered bright blood image group; establishing a contrast enhancement three-dimensional model by utilizing the K contrast enhancement images; obtaining an intracranial angiography enhanced three-dimensional model based on the blood three-dimensional model, the blood vessel three-dimensional model and the angiography enhanced three-dimensional model.

The invention discloses an intracranial vascular focus recognition method based on transfer learning. The method comprises the steps of acquiring a bright blood image group, a black blood image group and an enhanced black blood image group; preprocessing to obtain a first bright blood image and a first black blood image; taking the corresponding first black blood image as a reference for each first bright blood image, and obtaining a registered bright blood image group by using mutual information based on Gaussian distribution sampling and a registration method of an image pyramid; performing flow empty artifact elimination to obtain an artifact-eliminated enhanced black blood image group; subtracting corresponding images in the artifact elimination enhanced black blood image group and the black blood image group to obtain K contrast enhanced images; and establishing a blood three-dimensional model by utilizing the registered bright blood image group and adopting a transfer learning method, and establishing a blood vessel three-dimensional model of blood boundary expansion by utilizing the registered bright blood image group. The focus area of the intracranial blood vessel can be simply, conveniently, quickly and visually recognized clinically.

The invention discloses an intracranial blood vessel image registration method. The method comprises the following steps: acquiring a bright blood image and a black blood image of an intracranial blood vessel; taking the black blood image as a reference image and the bright blood image as a floating image, performing coordinate transformation on the bright blood image, and performing interpolationprocessing on the bright blood image by adopting a bicubic interpolation method; calculating the similarity between the bright blood image and the black blood image after interpolation processing byusing similarity measurement; finding out the optimal similarity measurement by utilizing a search strategy; according to the space transformation matrix, carrying out coordinate transformation on thebright blood image when similarity measurement is optimal, and obtaining a first registration image; and according to the scanning area of the bright blood image, extracting the same scanning area inthe black blood image to obtain a second registration image. According to the scheme, a doctor can be assisted in accurate intracranial disease diagnosis.

In various embodiments, the present invention teaches systems and methods for using T1-weighted black-blood MR imaging, with which a CVT can be well isolated from the surrounding tissues due to the signal suppression of flowing blood. In some embodiments, the invention teaches using black-blood imaging (3D variable-flip-angle turbo spin-echo acquisition) to directly visualize thrombi. In certain embodiments, the invention teaches using T1 weighted image contrast and isotropic sub-millimeter spatial resolution for accurate detection and staging of thrombi. In various embodiments, the invention allows for the detection of chronic thrombosis recanalization.

The invention discloses an intracranial blood vessel image registration method which comprises the steps of acquiring a plurality of image pairs to be registered of intracranial blood vessels, whereineach image pair comprises a bright blood image and an enhanced black blood image; preprocessing the bright blood image and the enhanced black blood image in each image pair to obtain a first bright blood image and a first black blood image of the image pair; selecting a part of preprocessed image pairs as test image pairs; performing image registration on the first bright blood image and the first black blood image in each test image pair by adopting a registration method based on mutual information and an image pyramid to obtain a rotation matrix corresponding to the first bright blood imagein the test image pair after registration; obtaining the mean value of the rotation matrixes of all the test image pairs; and performing coordinate transformation on the first bright blood images inother preprocessed image pairs except the test image pair by using the mean value of the rotation matrix to complete image registration. The method provided by the invention can improve the registration precision and registration speed of the intracranial blood vessel image.

The embodiment of the invention discloses a magnetic resonance black blood imaging method and system. The method comprises the steps that a preparation pulse module in a preset imaging sequence is utilized to excite a scanning object at the same time, and the scanning object comprises a first number of layers where blood flow signals are restrained; when the preset inversion time is reached, a second number of layers in the layers of which the blood flow signals are restrained are simultaneously excited by utilizing an acquisition imaging module in the preset imaging sequence, and interlayer aliasing magnetic resonance signals of the second number of layers are acquired; in a repetition time of the preset imaging sequence, black blood excitation and signal acquisition are repeatedly executed according to a third number, and interlayer aliasing magnetic resonance signals of a fourth number of layers are generated; and interlayer de-aliasing and image reconstruction are conducted on the interlayer aliasing magnetic resonance signals of the fourth number of layers to generate a magnetic resonance black blood image of each layer. By means of the technical scheme, collection of magnetic resonance signals in which multiple layers of blood flow signals are completely inhibited at the same time is achieved, and the magnetic resonance black blood imaging speed is increased.

The invention discloses a cerebrovascular image flow void artifact elimination method. The method comprises the steps of acquiring a bright blood image and an enhanced black blood image of the brain blood vessel; taking the enhanced black blood image as a reference image and the bright blood image as a floating image, performing coordinate transformation on the bright blood image, and performing interpolation processing on the bright blood image by adopting a bilinear interpolation method; calculating the similarity between the bright blood image after interpolation processing and the enhancedblack blood image by using similarity measurement; finding out the optimal similarity measurement by utilizing a search strategy; carrying out coordinate transformation on the bright blood image whenthe similarity measurement is optimal, and obtaining a first registration image; extracting the same scanning area in the enhanced black blood image according to the scanning area of the bright bloodimage in the first registration image to obtain a second registration image; and carrying out flow void artifact elimination on the second registration image. According to the scheme of the invention, the flow void artifact can be quickly eliminated, more accurate and comprehensive blood vessel images can be displayed, and doctors can be assisted in accurate intracranial disease diagnosis.