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AI Biotech/Diagnostics: Cardio
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Patent US10373315
Issued 2019-08-06
Method And System For Computer-aided Triage
A system for computer-aided triage can include a router, a remote computing system, and a client application. A method for computer-aided triage can include determining a parameter associated with a data packet, determining a treatment option based on the parameter, and transmitting information to a device associated with a second point of care.
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- 1. A method for computer-aided triage, the method comprising, at a remote computing system remote from a first point of care:
receiving, at the remote computing system, a set of Digital Imaging and Communications in Medicine (DICOM) brain images associated with a patient, wherein the set of DICOM brain images is concurrently sent to a standard radiology workflow operating in parallel with the method, wherein, in the standard radiology workflow, a radiologist analyzes the set of DICOM brain images and notifies a specialist based on a visual assessment of the set of DICOM brain images at a workstation, wherein the standard radiology workflow takes a first amount of time; at the remote computing system, automatically detecting a potential cerebral artery occlusion from the set of DICOM brain images, comprising:
segmenting a large vessel region from the set of DICOM brain images;
extracting a centerline from the large vessel region;
calculating a centerline length of the large vessel region based on the centerline, wherein calculating the centerline length comprises a centerline extension process;
comparing the centerline length with a predetermined threshold; and
detecting the potential cerebral artery occlusion when the centerline length is less than the predetermined threshold;
upon the potential cerebral artery occlusion detection, automatically:
determining, at the remote computing system, the specialist from the standard radiology workflow, wherein the specialist is associated with a second point of care;
notifying the specialist on a mobile device associated with the specialist, wherein the specialist is notified in a second amount of time shorter than the first amount of time, wherein the radiologist is not automatically notified upon potential cerebral artery occlusion detection;
displaying a compressed version of the set of DICOM brain images on the mobile device; and
displaying a high-resolution version of the set of DICOM brain images on a workstation associated with the specialist.
- 11. A method for augmenting a standard radiology workflow operating in parallel with the method, the method comprising, at a remote computing system remote from a first point of care:
receiving, at the remote computing system, a set of images of a brain of a patient, wherein the set of brain images is concurrently sent to the standard radiology workflow operating in parallel with the method, wherein, in the standard radiology workflow, a radiologist analyzes the set of images and notifies a first specialist in response to determining a presence of a large vessel occlusion; at the remote computing system, automatically detecting a potential large vessel occlusion from the set of images, comprising:
segmenting a large vessel region from the set of images;
extracting a centerline from the large vessel region;
calculating a centerline length of the large vessel region based on the centerline, wherein calculating the centerline length comprises a centerline extension process;
comparing the centerline length with a predetermined threshold; and
detecting the potential large vessel occlusion when the centerline length is less than the predetermined threshold;
upon the potential large vessel occlusion detection, automatically:
determining, at the remote computing system, a second specialist from the standard radiology workflow, wherein the second specialist is associated with a second point of care;
notifying the second specialist on a mobile device associated with the second specialist before the radiologist notifies the first specialist; and
displaying a compressed version of the set of images on the mobile device.
