17 results about "Computed tomography angiography" patented technology

The invention relates to the technical field of medical data processing, and discloses a non-invasive hemodynamic assessment system for coronary artery stenosis degree, comprising an image acquisition module used for acquiring a coronary artery computed tomography angiography image of a patient; the physiological signal acquisition module is used for synchronously acquiring physiological signals of a patient, and the physiological signals comprise electrocardiosignals and non-invasive arterial blood pressure signals; and the data processing module is used for preprocessing and segmenting the coronary artery computed tomography angiography image. Electrocardiogram and non-invasive arterial blood pressure signals are collected through the sensor, risks and complications caused by invasive examination of traditional coronary artery radiography are avoided, the problem that patients unsuitable for invasive examination such as contrast agent allergy and renal insufficiency are difficult to evaluate is solved, the pain of the patients is relieved, and the acceptability of the patients is improved.

Detection of landmarks in volumes of medical images is an important step in developing various diagnostic procedures. The invention pertains to a method detection of a landmark in a volume of medical images. Said volume of medical images can be selected from a computational tomography volume or a magnetic resonance volume. The invention includes a residual U-Net architecture to produce a heatmap that describes probability of finding the landmark which can be combined with a 3D Differentiable Spatial to Numerical Transform (DSNT) in order to obtain coordinates of the landmark. The invention was evaluated on two datasets: dataset containing 157 Coronary Computed Tomography Angiography (CCTA) scans and a dataset containing 77 Computed Tomography Angiography (CTA) scans. The proposed method provides a significantly improve accuracy of landmark detection, especially for ostium landmark detection, when compared to known methods.

A method of analyzing computed tomography (CT) images comprises receiving an initial CT image of an object, identifying calcium-free regions and a calcified region in the initial CT image of the object, generating a calcium-free image patch, and applying the calcium-free image patch to the initial CT image patch to produce a final CT image. The initial CT image shows a calcium deposit and a target structure in the object. The calcified region in the initial CT image shows the calcium deposit in the object obscuring a portion of the target structure. The calcium-free regions show the remaining portions of the target structure. The calcium-free image patch corresponds to the calcified region in the initial CT image. The final CT image shows the calcium-free image patch and the calcium-free region from the initial CT image. The calcium-free image patch is generated and applied using a convolutional neural network.

The invention relates to a contrast-agent-free angiography generation system and method based on mask guidance, a parameter optimization device is used for performing parameter optimization on a conversion device by utilizing a loss function capable of highlighting a contrast agent shadow, and the capability of capturing complex image details of the conversion device is improved. Then, the Gaussian noise image is fused into a contrast-agent-free computed tomography image through a conversion device, computed tomography angiography is obtained through a fusion mode of feature sampling and gradual denoising, and it is guaranteed that the obtained computed tomography angiography has enough consistency and sense of reality; and the sharpness and fidelity of the generated vascular structure are improved.

The invention relates to the technical field of medical image processing, in particular to a multilevel vascular network reconstruction and segmentation method based on drainage basin analysis, which comprises the following steps: acquiring a 3D CT (three-dimensional computed tomography angiography) scanning result; based on the 3DCTA scanning result, reconstructing a 3D blood vessel network; performing image segmentation and enhancement processing on the 3DCTA scanning result to obtain an original blood vessel center line; constructing a pressure field based on the original blood vessel center line; determining a watershed position in the blood vessel network based on the pressure field; segmenting the blood vessel network according to the watershed position; and outputting a reconstructed 3D blood vessel network and a blood vessel segmentation result, and by ingeniously combining a drainage basin analysis theory and a traditional image processing technology, considering the geometric morphology and hemodynamic characteristics of the blood vessel in the blood vessel reconstruction and segmentation process. The accuracy of reconstruction and segmentation is improved, and a new view angle is provided for vascular function evaluation.

The invention relates to the technical field of medical image processing, and relates to an aortic dissection noninvasive blood flow velocity measurement method, system and device and a storage medium. The aortic dissection noninvasive blood flow velocity measurement method comprises the following steps: acquiring four-dimensional computed tomography angiography image data to be detected; analyzing the four-dimensional computed tomography angiography image data by using an optical flow method to obtain an aorta blood flow velocity field; analyzing the four-dimensional computed tomography angiography image data, segmenting an aorta image and extracting a center line of the aorta; determining the open area of each position of the aorta according to the aorta image and the center line of the aorta; and determining the instantaneous flow velocity of each position of the aorta according to the aorta blood flow velocity field and the overflowing area of each position of the aorta to obtain a blood flow velocity measurement result. According to the invention, the blood flow velocity of the aorta can be accurately identified.

This invention discloses a preoperative risk prediction method for cerebral aneurysms based on multimodal deep learning. To address the problems of time-consuming computational fluid dynamics simulations and difficulty in quickly obtaining individualized hemodynamic indicators, this invention reconstructs vascular geometry and a tree diagram by aligning computed tomography angiography, magnetic resonance angiography, and blood pressure and heart rate time series. It employs a graph network that satisfies Kirchhoff conservation and connects differentiable Wendt-Kessel impedance learning boundary conditions. Combining physical constraints of cardiac phase conditional neural operators, Helmholtz projection, and signed distance function boundary embedding, it approximates the flow field, calculates and closes the loop to correct wall shear stress, oscillatory shear exponent, and pressure gradient. Then, it fuses the risk features of the imaging branch, clinical branch, and text branch through expert product to output lesion-level and patient-level risks and confidence levels. This achieves the technical effect of rapidly estimating hemodynamics and performing interpretable preoperative risk assessment under physically consistent constraints.

The invention discloses a myocardial perfusion quantitative evaluation method. The method comprises the following steps: acquiring an X-ray angiography image target sequence and a computed tomography angiography image of a target blood vessel; determining the volume of a target blood vessel of each X-ray radiography image in the X-ray radiography image target sequence, obtaining the maximum volume and the minimum volume of the target blood vessel from the beginning of filling to the end of filling, and further determining a blood flow volume, and recording the blood flow volume as an initial blood flow volume; according to the computed tomography angiography image, determining the mass or volume of the myocardial area perfused by the target blood vessel to obtain the mass or volume of the target myocardial; carrying out image fusion, and further determining the distribution condition of the target blood vessel on the myocardium; determining target blood flow corresponding to the target blood vessels according to the initial blood flow and the distribution condition of the target blood vessels on the myocardium, and further calculating a quantitative myocardial perfusion value. The method can accurately obtain the quantitative myocardial perfusion value. The invention further discloses a myocardial perfusion quantitative evaluation device, electronic equipment and a storage medium.

The present specification provides a method for providing information on angiography for contrast reduction performed by a processor, comprising the steps of: receiving a computed tomography angiography (CTA) projection image of an individual and said CTA contrast agent concentration data; selecting one of a first model for each contrast agent concentration that is trained to generate a first extracted image of a blood vessel using the projection image of the CTA as input based on said contrast agent concentration data; generating a first extracted image using the received projection image as input to the selected first model; and generating a rendering image from said first extracted image.

The present invention relates to a mask-guided, contrast-free angiography generation system and method. A parameter optimization device optimizes the parameters of a conversion device using a loss function that emphasizes contrast-enhanced shadows, improving the conversion device's ability to capture complex image details. The conversion device then integrates a Gaussian noise image into a contrast-free computed tomography image, and a computed tomography angiography is generated through a fusion of feature sampling and progressive denoising. This ensures sufficient consistency and realism in the resulting computed tomography angiography, improving the sharpness and fidelity of the generated vascular structures.

Calcific and noncalcific aortic tissue components can be quantified. Pre-intervention planning computed tomography angiography imaging data is received. A region of interest is defined between the lower coronary ostium and the virtual basal ring. Cross-sectional images of the region of interest are rendered and calcific and noncalcific tissue components are identified based on Hounsfield unit thresholds. The volumes of the identified calcific and noncalcific tissue components are calculated and used to determine a total tissue volume (e.g., fibrocalcific volume) for the valve, as well as component percentages of the total tissue volume for the calcific and noncalcific components. These volumes and / or component percentages can be leveraged to predict severe AS, identify prognosis of post-TAVI outcomes, or otherwise facilitate planning of medical intervention.

In the present specification, as an information providing method for angiography which is implemented by a processor, an information providing method for angiography including a step of receiving a projection image of a computed tomography angiography (CTA) of an individual, a step of generating a first extraction image for a blood vessel by inputting the received CTA projection image to a first model which is trained to generate a first extraction image for the blood vessel with a CTA projection image as an input, and a step of generating a rendering image from the first extraction image.

The application relates to the technical field of medical image processing, and relates to an aortic dissection noninvasive blood flow velocity measurement method, system, device and storage medium; the aortic dissection noninvasive blood flow velocity measurement method comprises the following steps: acquiring four-dimensional computed tomography angiography image data to be detected; analyzing the four-dimensional computed tomography angiography image data by using an optical flow method to obtain an aortic blood flow velocity field; analyzing the four-dimensional computed tomography angiography image data, segmenting an aortic image and extracting a center line of the aorta; determining the flow area of each position of the aorta according to the aortic image and the center line of the aorta; determining the instantaneous flow velocity of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta, and obtaining a blood flow velocity measurement result. The application can accurately identify the blood flow velocity of the aorta.

Embodiments herein rapidly transform computed tomography angiography (CTA) data into an interactive, holographic visualization for clinical use. In one embodiment, a system for visualizing computed tomography angiography (CTA) images comprises a data interface configured to receive CTA image data in a Digital Imaging and Communications in Medicine (DICOM) format. The system also comprises a processor configured to render a plurality of two-dimensional CTA slice images into a three-dimensional (3D) volumetric dataset from the CTA image data, to filter the 3D volumetric dataset to resolve vascular structures relative to surrounding tissue and bone, and to generate an extended reality (XR) holographic representation of the filtered 3D volumetric dataset. The system also comprises an XR display device configured to present the holographic representation to a user for the user to manipulate the holographic representation and identify a vascular abnormality.

The present invention relates to the field of medical image processing technology, and more specifically, to a multi-level vascular network reconstruction and segmentation method based on watershed analysis. The method comprises the following steps: obtaining three-dimensional computed tomography angiography (3D CTA) scan results; reconstructing a 3D vascular network based on the 3D CTA scan results; performing image segmentation and enhancement processing on the 3D CTA scan results to obtain original vascular centerlines; constructing a pressure field based on the original vascular centerlines; determining watershed locations in the vascular network based on the pressure field; segmenting the vascular network based on the watershed locations; and outputting the reconstructed 3D vascular network and vascular segmentation results. By cleverly combining watershed analysis theory with traditional image processing techniques, the vascular reconstruction and segmentation process simultaneously considers both vascular geometry and hemodynamic characteristics. This method not only improves the accuracy of reconstruction and segmentation but also provides a new perspective for vascular function assessment.

Systems and methods are provided for automated image analysis of volumetric image data depicting blood vessels. Volumetric imaging data, such as computed tomography angiography data, are processed by an image segmenter implemented as a convolutional neural network to generate a lumen mask identifying vessel lumen within the volumetric image data. In implementations, the image segmenter predicts binary masks on multiple two-dimensional slices extracted from the volumetric image data along different axes and / or angles, and the predicted masks are combined by voting, averaging, and / or nonlinear filtering to form a three-dimensional lumen segmentation. A three-dimensional segmented vessel model is formed from the lumen segmentation, a narrowing region is detected, and dimensional parameters of the narrowing region are computed, including at least stenosis length, stenosis thickness, and minimum lumen cross-sectional area. The dimensional parameters are output in a machine-readable format. Optionally, computational flow parameters and classification outputs may be generated.

Provided in the present description are a vascular projection visualization method and apparatus, and a storage medium and an electronic device. The method comprises: acquiring a first image of a target region by computed tomography angiography and a second image of the target region by digital subtraction angiography; determining a vascular path and a plaque region in the first image, and constructing a mesh structure of the vascular path; on the basis of a positional relationship between the mesh structure and the plaque region in the first image, obtaining an occlusion relationship between the mesh structure and the plaque region; and on the basis of the occlusion relationship, rendering a mesh structure and the plaque region in the second image, so as to obtain a fused image. A mesh structure of a vascular path is constructed, and on the basis of an occlusion relationship between the mesh structure and a plaque region, the mesh structure and the plaque region are rendered in a second image to obtain a fused image, such that a positional relationship between the mesh structure and the plaque region in a mapping direction of the second image is intuitively reflected while the degree of vascular stenosis, the degree of vascular dilation, and the location of a plaque are displayed.