METHOD AND SYSTEM FOR COMPUTER-AIDED ANEURYSM TRIAGE
A system for computer-aided triage includes and/or interfaces with a computing system. A method for computer-aided triage includes receiving a data packet including a set of images; and processing the set of images to determine a suspected condition and/or associated features. Additionally or alternatively, the method can include any or all of: preprocessing the set of images; triggering an action based on the suspected condition and/or associated features; determining a recipient based on the suspected condition; preparing a data packet for transfer; transmitting information to a device associated with the recipient; receiving an input from the recipient and triggering an action based on the input; aggregating data; and/or any other suitable processes.
1 . A system for computer-aided detection and decision-making associated with a suspected pathology, the system comprising:
a computing subsystem, wherein the computing subsystem:
receives a set of images associated with a patient;
processes the set of images with a set of trained models to automatically identify the suspected pathology;
identifies a set of specialists based on based on the suspected pathology; and
transmits, to each application of a set of applications, a notification and a set of compressed images comprising a compressed version of the set of images; and
the set of applications, each application executing on a mobile user device associated with a specialist in the set of specialists, wherein each application is configured to display the notification, wherein each application comprises:
a viewer displaying the set of compressed images; and
a messaging center configured to transmit messages between specialists in the set of specialists.
2 . The system of claim 1 , wherein the suspected pathology is a suspected aneurysm with a diameter greater than a threshold.
3 . The system of claim 1 , wherein the threshold is 5 mm.
4 . The system of claim 1 , further comprising a diagnostic viewing system configured to:
display the set of images; and
receive an input from a diagnostic specialist, the input comprising a confirmation of the suspected pathology, wherein the computing subsystem transmits the notification in response to receiving the input.
5 . The system of claim 4 , wherein the patient is in a queue of patients, wherein the diagnostic viewing system is configured to display a set of images for each patient in the queue, wherein the queue is prioritized based on a suspected pathology, identified at the computing subsystem, for each patient in the queue.
6 . The system of claim 1 , wherein the notification is concurrently transmitted to each application in the set of applications.
7 . The system of claim 1 , wherein each application monitors for an input from the specialist associated with the application and performs an action in response to receiving the input.
8 . The system of claim 7 , wherein the input comprises a read receipt.
9 . The system of claim 7 , wherein the input comprises a request to initiate a transfer of the patient.
10 . The system of claim 7 , wherein the input comprises an acceptance to treat of the patient.
11 . The system of claim 1 , wherein the compressed set of images comprises a subset of the first set of images.
12 . The system of claim 1 , wherein the viewer displays annotations comprising a measurement for the suspected pathology.
13 . A method for computer-aided detection and decision-making associated with a suspected pathology, the method comprising:
receiving a set of images associated with a patient;
processing the set of images with a set of trained models to automatically identify a set of suspected aneurysms; and
for each suspected aneurysm in the set of suspected aneurysms:
determining a set of measurements for the suspected aneurysm; and
annotating the set of images, comprising coloring a region of the set of images based on a size threshold, the set of measurements, and a location of the suspected aneurysm.
14 . The method of claim 13 , wherein, for each suspected aneurysm, the region of the set of images is further colored based on a second size threshold.
15 . The method of claim 13 , wherein, for each suspected aneurysm, the size threshold comprises at least one of a diameter threshold or a volume threshold.
16 . The method of claim 13 , wherein, for each suspected aneurysm, annotating the set of images further comprises annotating the set of images with the set of measurements.
17 . The method of claim 16 , wherein, for each suspected aneurysm, the set of measurements comprises a volume of the suspected aneurysm.
18 . The method of claim 17 , wherein, for each suspected aneurysm, the volume is determined based on a probability score associated with each voxel corresponding to the suspected aneurysm.
19 . The method of claim 13 , further comprising predicting a feature of a suspected aneurysm in the set of suspected aneurysms, the feature corresponding to a future time.
20 . The method of claim 13 , wherein the first set of images are associated with a first time, the method further comprising:
receiving a second set of images associated with a patient, the second set of images associated with a second time, wherein the set of suspected aneurysms have progressed between the first time and the second time; and
determining a comparison based on the first set of images and the second set of images.