US 12,109,025 B2
System and method for detecting a health condition using eye images
Mohamed Sheta, Vancouver (CA); Benjamin Fonooni, Vancouver (CA); Sara Leblanc, Vancouver (CA); and Lingxiao Qi, Vancouver (CA)
Assigned to AIZTECH CANADA INC., Vancouver (CA)
Filed by AIZTECH CANADA INC., Vancouver (CA)
Filed on Jun. 2, 2023, as Appl. No. 18/205,296.
Application 18/205,296 is a continuation in part of application No. PCT/CA2021/051718, filed on Dec. 2, 2021.
Claims priority of provisional application 63/277,372, filed on Nov. 9, 2021.
Claims priority of provisional application 63/121,683, filed on Dec. 4, 2020.
Prior Publication US 2023/0346276 A1, Nov. 2, 2023
Int. Cl. A61B 5/16 (2006.01); G06F 3/01 (2006.01); G06V 40/18 (2022.01)
CPC A61B 5/163 (2017.08) [G06F 3/013 (2013.01); G06V 40/18 (2022.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method for predicting whether a user has a target health condition using eye images, the method comprising:
providing automated guidance to the user to obtain, using a computing device operated by the user, a plurality of images including the user's sclera, each of the images corresponding to a guided direction of the user's gaze;
receiving the images from the computing device by way of a network;
verifying that the images sufficiently show the user's sclera, including by estimating a direction of the user's gaze and confirming that the estimated direction for a given one of the images conforms with the guided direction corresponding to that image;
generating feature-enhanced image data by:
extracting an eye image of the user from at least one image from the plurality of images;
masking an iris area of the extracted eye image of the user in the at least one image such that the iris area of the extracted eye image is absent from downstream processing; and
applying an autoencoder to enhance features corresponding to the user's sclera in the at least one image to generate the feature-enhanced image data; and
computing a prediction of whether the user has the target health condition by providing the feature-enhanced image data to a convolutional neural network (CNN), wherein the feature-enhanced image data comprises image data representing ocular manifestations in the user's sclera and outside of the masked iris area in the extracted eye image in the at least one image, wherein the target health condition is related to coronavirus, and the CNN comprises a plurality of layers including a convolutional layer, an non-linear activation layer and a max-pooling layer.