41 results about "Left ventricular myocardium" patented technology

Methods, systems and circuits predict cardiotoxicity induced cardiac injury prior to an irreversible state by electronically generating at least one histogram of mean intensities of voxels / pixels in an MRI image of a left ventricle myocardium and electronically determining a likelihood of cardiac injury due to cardiotoxicity based on data from the at least one histogram.

The invention provides a division method and device of left ventricular myocardium. The method comprises the following steps of: (1) positioning a left ventricular central point, and acquiring a region of interest in an image at a layer where the left ventricular central point is located; (2) positioning a blood pool region in the region of interest in the image at the layer where the left ventricular central point is located according to grey scale information and the left ventricular central point; (3) determining a mass center of the blood pool region, determining blood pool regions in an original image in all layers except the layer where the left ventricular central point is located, thereby obtaining a division result of left ventricular endocardium; and (4) obtaining a division result of left ventricular adventitia by a dynamic planning method according to the division result of the left ventricular endocardium, and thus obtaining a division result of the left ventricular myocardium. By the technical scheme provided by the invention, the left ventricular myocardium can be fully, uniformly and stably divided.

The invention relates to a fusion method for a coronary artery CT image and a cardiac ultrasonic strain image. The invention provides a multi-mode image fusion technology method for fusing and mappinga two-dimensional UCG image and a three-dimensional CT image to stereoscopically display coronary artery lesions and myocardial damage conditions. According to the method, The cardiac ultrasonic image and the CT image are fused for the first time; the ultrasonic cardiogram and the coronary artery CT image are fused (figure 1) through a one-point one-surface three-section positioning method; and athree-dimensional pattern diagram is displayed. Then, on the basis of a three-dimensional ultrasonic volume image, two-dimensional images (figure 2) of 20 sections and 480 grid segments of a left ventricular myocardium are obtained by adopting a central axis rotation method and a refined segmentation method; based on this, the strain values of 480 segments are obtained; and myocardial perfusion ischemia information obtained by three-dimensional strain is superimposed into the three-dimensional coronary artery vascular pattern diagram (figure 3), thereby accurately reflecting a relation between a myocardial ischemia area and an actual coronary artery stenosis.

The invention belongs to the field of medical image processing, and discloses a method and a system for quantitatively evaluating myocardial infarction on the basis of nuclide image and CT (computed tomography) coronary angiography fusion. The method includes acquiring heart PET (positron emission tomography) / CT and CTA (computed tomography angiography) data; carrying out three-dimensional DCT (discrete cosine transformation) frequency-domain interpolation on PET / CT images; acquiring heart regions in the PET / CT images and CTA images by the aid of multi-spectrum segmentation processes; acquiring left ventricular cardiac muscle regions in PET images by the aid of threshold processes; manually segmenting left ventricular cardiac muscle regions in the CTA images layer by layer; registering images; classifying pixel points according to the locations of pixel points on the registered images and tracer uptake values; inversely transforming infarction regions into original CTA spaces and dividing the volumes of left ventricular cardiac muscles from the volumes of the transformed infarction regions; three-dimensionally displaying fused images in volume rendering manners. The method and thesystem have the advantages that integral registration procedures can be fully automated, the method and the system are good in objectivity, intuitive results can be obtained, and analysis can be facilitated for clinical doctors.

The invention discloses a method for processing a cardiac perfusion magnetic resonance image. The method comprises the steps of: acquiring magnetic resonance images INT of a plurality of layers of slices including left ventricular myocardium; from the start layer, respectively segmenting the myocardial inner membrane of the magnetic resonance images of the N layers of slices within T heartbeat cycles to obtain a reference image Imr corresponding to each layer of slice; based on the reference image Imr, registering the magnetic resonance image of the current layer of slice within the T heartbeat cycles; based on the segmentation result of the myocardial inner membrane of the magnetic resonance image of each layer of slice, segmenting a myocardial outer membrane; calculating and smoothing a mean gray-time curve of a left ventricular cavity zone and a right ventricular cavity zone; and taking the connecting line of the centroid point of a blood pool zone defined by the myocardial inner membrane and the center point of a right ventricular boundary as a base line, blocking the myocardium according to a bovine eye graph partitioning method. The method can realize visual and full-automatic quantitative analysis on the signal intensity change curve of the left ventricular myocardium with time.

The invention provides a heart segmentation model and pathology classification model training, heart segmentation and pathology classification method and device based on heart MRI (Magnetic Resonance Imaging), and the method comprises the steps: suppressing a residual background part with a small pixel gray level change through a standard deviation filter, highlighting a left ventricle, a right ventricle and a myocardial ,the central position of the left ventricular myocardial wall being further obtained through canny edge detection and circular Hough transform, drawing a rectangular mask, the two-dimensional image being cut based on the rectangular mask to serve as input for training a preset neural network model for training. Background interference can be greatly inhibited, and fast convergence of neural network training is promoted. The pathology classification model training method comprises the following steps: segmenting a two-dimensional image obtained by segmenting each frame of cardiac magnetic resonance imaging short axis in a cardiac cycle based on a cardiac segmentation model, calculating classification feature values, and constructing a random forest based on the classification feature values of a plurality of samples and pathology classification to obtain a cardiac pathology classification model; and realizing automatic pathological classification.

The invention relates to medicine, namely: to cardiology, and may be used for assessment of functional condition of the human cardiovascular system (CVS) and the character of its control by the autonomic nervous system and other regulatory systems of the homeostasis. A method of non-invasive examination of the human CVS was developed, the method enabling to continuously, during a necessary period of time and quite simply with the aid of a computer and a piezoceramic tranducer (FIG. 3), record differential sphygmograms (FIG. 4) and by these sphygmograms using the method of determining the “coding” points to perform express-analysis simultaneously of two main pulse characteristics: a) rhythmicity and b) pulse oscillation of the arterial pressure (AP). The automatic disposition of the “coding” points in the averaged graph of the cardiocycle and their additional visual correction (FIG. 5) guarantee precision of determining the amplitude-temporal parameters at each recognised normal pulsation of a selected pulsogram fragment. By this fragment, the cardiac rhythm and all the amplitude-temporal cardiohemodynamic parameters will be measured and analysed, the parameters characterising the left ventricle myocardium contractile capacity as well as the resilient-elastic properties of the arterial bed vessel walls. For this purpose, the conventional units of the computer “digitizing” will be calibrated and transformed into accepted units of the blood AP measurement (mm Hg) and then, by means of integrating by respective areas of the cardiocycle graphs, the values of the blood AP pulse increment will be determined for different stages of the cardiac cycle. The continuous monitoring of the pulsogram parameter changes provides fulfillment of spectral analysis of the cardiac rhythm variability as well as of the selected cardiohemodynamic parameters. By results of the statistical and spectral analyses of the measured parameters' variability, the functional condition and the character of the subject's CVS vegetative regulation will be assessed by comparing the obtained values with the average statistical numerical values of these same parameters established for the CVS of groups of people who were selected as control subjects. The results may be used for resolving the problems of differential diagnosis of the cardiovascular diseases under clinical conditions, for individual examination of patients as well as for performing an operative medical checkup of health condition in various groups of population.

The invention is directed to a heart stimulator for left-ventricular pacing comprising a left ventricular stimulation pulse generator connected or connectable to a single electrode lead for left ventricular stimulation having one or more electrodes for delivery of stimulation pulses to left ventricular myocardial heart tissue, said stimulation pulse generator being adapted to generate and deliver stimulation pulses of switchable polarity. The heart stimulator further comprises a control unit connected to the stimulation pulse generator for controlling the stimulation pulse generator and to trigger generation and delivery of stimulation pulses having a polarity controlled by said control unit, wherein the control unit is adapted to control said left ventricular stimulation pulse generator so as to deliver at least a pair of suprathreshold stimulation pulses of opposite polarity.

The invention relates to a cardiac medical image processing method, a processing device, a processing system and a medium. The method comprises the following steps: receiving a cardiac medical image of a left ventricle long-axis section; utilizing the trained first learning network to identify mitral valve base points and apex apexes on two sides of the left ventricle and the outer edge and the inner edge of the left ventricle myocardium; arranging an upper edge by utilizing a first connecting line of a mitral valve base point; defining the left ventricular myocardium by the upper edge, the inner edge and the outer edge, using the midpoint of the first connecting line and the second connecting line of the apex of the left ventricular as the midline, evenly dividing the parts, on the two sides of the midline, of the left ventricular myocardium into n parts, and therefore the left ventricular myocardium is divided into 2n sections. According to the cardiac medical image processing method, the processing device, the processing system and the medium, each cardiac muscle area can be automatically, accurately and quickly drawn and identified, the workload of doctors is greatly reduced, and automatic identification of the cardiac medical image processing device can continuously benefit from a training data set marking the cardiac muscle areas through training.

The invention belongs to the technical field of biological pharmacy, and discloses a medicine for resisting pressure overload myocardial hypertrophy and ventricular remodeling and application. The application comprises the following steps of: establishing a pressure overload rat myocardial hypertrophy and ventricular remodeling animal model by adopting abdominal aorta constriction; constricting the abdominal aorta for 28d, and sequentially detecting the change of a hemodynamic index and the diameter of a myocardial cell; and transecting the left ventricular myocardial tissue of a rat, observing the form of the myocardial cell under an optical microscope after conventional HE staining, and observing the change effect of leonurine on the pathological form of the left ventricular myocardial tissue of the rat. The invention proves that high and low dosage groups of leonurine have a certain improvement effect on cardiac diastolic and systolic dysfunction of a myocardial hypertrophy rat induced after abdominal aorta constriction; the high and low dosage groups of leonurine can reduce the left ventricular hypertrophy index of the rat after AAC operation; and the high and low dosage groups of leonurine and a positive group can inhibit myocardial cell hypertrophy of the rat after AAC operation and inhibit ventricular remodeling.

The present invention relates generally to the use of erythropoietin (EPO) to facilitate resuscitation from cardiac arrest. For a mammalian subject suffering from cardiac arrest, concurrent administration of EPO with resuscitation after the onset of ventricular fibrillation facilitates the resuscitation. Administration of EPO serves to attenuate myocardial abnormalities caused by cardiac arrest and the resuscitation efforts and favor improved resuscitation outcomes. The main effect of EPO that facilitates resuscitation is the preservation of left ventricular myocardial distensibility leading to improve left ventricular preload and the amount of blood ejected by chest compression. This effect enables higher coronary perfusion pressures to be generated resulting in a higher rate of return of spontaneous circulation and higher survival rates. The very same effect enables the return of spontaneous circulation to occur faster reducing the time a human subject is in cardiac arrest. These effects lead to a higher number of cardiac arrest victims to survive and to do so with intact neurological function in most of the survivors.

The invention relates to a cardiac medical image processing device, a processing system and a medium. The processing device comprises a processor, configured to identify a mitral valve basal point, acardiac apex vertex and outer and inner edges of a left ventricular myocardium by using a first learning network based on a heart image of a long-axis section; arrange an upper edge by utilizing a first connecting line of the mitral valve base point; define the left ventricular myocardium by the upper edge, the inner edge and the outer edge, the second connecting line of the midpoint of the firstconnecting line and the apex serves as the midline, evenly divide the left ventricular myocardium on the two sides, and achieve segment division; determine a first strain condition of each section inthe long-axis section, wherein the first strain condition comprises an area change condition of the corresponding section; and determining a second strain condition of the corresponding segment in thevertical direction based on the area change condition of each segment. All myocardial segments can be automatically, accurately and rapidly recognized, the global or local three-dimensional strain condition of the left ventricle can be determined, and myocardial strain and functional conditions can be conveniently and comprehensively evaluated.

The present disclosure relates to a processing method, a processing device, a processing system and a medium for cardiac medical images. The method includes: receiving a cardiac medical image of a long-axis view of the left ventricle; using a trained first learning network to identify the mitral valve base points on both sides of the left ventricle, the apex apex, and the outer edge and inner edge of the left ventricular myocardium; The first connecting line of the mitral valve base point, set the upper edge; use the upper edge, inner edge and outer edge to enclose the left ventricular myocardium, and use the midpoint of the first connecting line and the second connecting line of the apex of the left ventricle as the midline , the parts of the left ventricular myocardium on both sides of the midline are evenly divided into n parts, thereby dividing it into 2n segments. The processing method, processing device, processing system and medium of the cardiac medical image can automatically, accurately and quickly delineate and identify various myocardial regions, greatly reducing the workload of doctors, and its automatic identification can continue to benefit from the labeling of myocardial regions after training training data set.

The invention provides a division method and device of left ventricular myocardium. The method comprises the following steps of: (1) positioning a left ventricular central point, and acquiring a region of interest in an image at a layer where the left ventricular central point is located; (2) positioning a blood pool region in the region of interest in the image at the layer where the left ventricular central point is located according to grey scale information and the left ventricular central point; (3) determining a mass center of the blood pool region, determining blood pool regions in an original image in all layers except the layer where the left ventricular central point is located, thereby obtaining a division result of left ventricular endocardium; and (4) obtaining a division result of left ventricular adventitia by a dynamic planning method according to the division result of the left ventricular endocardium, and thus obtaining a division result of the left ventricular myocardium. By the technical scheme provided by the invention, the left ventricular myocardium can be fully, uniformly and stably divided.

The invention discloses a method for segmenting the endocardium and the epicardium in a heart cardiac function magnetic resonance image. The method comprises positioning the diastasis in heart magnetic resonance images I<NP> including several lamellas of the left ventricular myocardium and in different cardiac cycle phases, and obtaining a coarse segmentation result of blood pools of magnetic resonance images of N lamellas in the diastasis; converting image data in the left ventricle region-of-interest in the magnetic resonance image of each lamella in the diastasis into a two-dimension polar coordinate conversion image by means of ray scanning based on a polar coordinate conversion method; detecting the endocardium and the epicardium in the two-dimension polar coordinate conversion image based on a bidynamic programming method; obtaining the endocardium and the epicardium in an original lamella image by means of polar coordinate inverse conversion, calculating the convex hull and smoothing the convex hull, and completing segmentation of the endocardium and the epicardium in the magnetic resonance images of the N lamellas in the diastasis; and deriving the segmentation result of the in the endocardium and the epicardium in the magnetic resonance images in the diastasis to the endocardium and the epicardium in the magnetic resonance images in other cardiac cycle phases.