Application US20190298204 AI Biotech/Diagnostics: Cardio

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Application US20190298204

Published 2019-10-03

Systems And Methods For Digitizing Electrocardiograms

The disclosure relates to systems and methods of converting a representation of a physiological signal (e.g., a non-digitized version such as a printed curve) into a digitized representation of the physiological signal of a subject. For example, a printed electrocardiogram (ECG) may be digitized using the systems are methods provided herein. The method may include receiving a digitized image of a printed curve representing the physiological signal of the subject, and detecting at least one region of interest having a portion of the physiological signal. For each of the regions of interest, the method may include extracting coordinates representing the physiological signal and registering the extracted coordinates.

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3 Independent Claims

1. A method for digital conversion of a printed representation of a physiological signal of a subject, the method comprising: receiving a digitized image of the printed representation of the physiological signal of the subject; detecting, via a first neural network, a layout region of the digitized image and at least one sub-region dividing the layout region; detecting, via a second neural network, at least one region of interest inside one of the identified sub-regions comprising a portion of the physiological signal; and extracting, via a third neural network, coordinates representing the physiological signal for each of the at least one region of interest.
11. A method for digital conversion of a printed representation of a physiological signal of a subject, the method comprising: receiving a digitized image of a printed representation of a physiological signal; detecting a layout region; dividing the layout region into at least one sub-region; generating at least one characteristic dimension of the layout region, a position of the layout region, and a number sub-regions; for each of the at least one sub-regions, segmenting, via a segmentation neural network, at least one region of interest comprising a portion of the physiological signal, wherein an input of the segmentation neural network is an image of the at least one sub-region and an output comprises a dimensions and a position of the at least one region of interest, and a probability of the presence of a portion of the physiological signal in the at least one region of interest; and for each region of interest, extracting, via an extraction neural network, coordinates representing the physiological signal.
20. A system for conversion of a printed curve representing a physiological signal of a subject into a digitized curve, the system comprising instructions stored on at least one processor, the instructions configured to, when executed, cause the at least one processor to: receive a digitized image of a printed curve representing the physiological signal of the subject; detect, via a first neural network, a layout region of the digitized image and at least one sub-region dividing the layout region; detect, via a second neural network, at least one region of interest comprising a portion of the physiological signal inside one of the at least one sub-region; and extract, via a third neural network, coordinates representing the physiological signal for each of the at least one region of interest.