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44 results about "Cardiac pathology" patented technology

Multi-Channel System for Beat to Beat QT Interval Variability

The measurement of beat-to-beat QT interval variability (QTV) shows clinical promise for identifying several types of cardiac pathology. However, until now, there has been no device capable of displaying, in real time on a beat-to-beat basis, changes in QTV in all 12 conventional leads in a continuously monitored patient. While several software programs have been designed to analyze QTV, heretofore, such programs have all involved only a few channels (at most) and/or have required laborious user interaction or off-line calculations and post-processing, limiting their clinical utility. This invention discloses a PC-based ECG software program that in real time, acquires, analyzes and displays QTV and PQ interval variability (PQV) in each of the independent channels that constitute the 12-lead conventional and/or Frank X, Y, Z lead ECG. The system also analyzes and displays the QTV and PQV from QT and PQ interval signals that are derived from multiple channels and from singular value decomposition such that the effect of noise and other artifacts on the QTV and PQV results are substantially reduced compared to existing single-channel methods. Moreover, this invention also discloses certain new parameters of T-wave (and QRS and P-wave) morphology, that in initial studies have improved clinical diagnostic utility and/or reproducibility and reliability compared to known existing parameters of T-wave morphology. Finally, it also discloses a method for determining the beat-to-beat variability these T, QRS and P-wave morphologic parameters.
Owner:CARDIOSOFT

Heart segmentation model and pathological classification model training, heart segmentation and pathological classification method and device based on heart MRI (Magnetic Resonance Imaging)

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.
Owner:PEKING UNION MEDICAL COLLEGE HOSPITAL CHINESE ACAD OF MEDICAL SCI
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