Method for monitoring thyroid eye disease condition, and system for performing same

A method for estimating eye protrusion value of a subject, performed by one or more processors, comprising:

• receiving, by a communication unit, a frontal facial image representing at least both eyes of the subject,
• wherein the frontal facial image comprises a plurality of pixels, the each of the plurality of pixels comprises at least one of pixel values, wherein the pixel values are not depth value which indicates calculated distance information;
• obtaining, by pre-processing the frontal facial image, an input data related to a facial image representing an area between an upper end of an eyebrow and lower end of a nose, wherein the pre-processing the frontal facial image comprises at least detecting facial landmarks positioned in the frontal facial image by using pre-trained facial landmark detection model;
• and
• estimating an eye protrusion value for the subject by applying the input data to a pre-trained eye protrusion value estimation model, wherein the eye protrusion value is a classification result indicating whether the subject has proptosis, wherein the pre-trained eye protrusion value estimation model is trained using a set of training input data and label data, wherein the training input data and label data are obtained on at least one clinical site by medical staff, wherein the training input data comprises a clinical frontal facial image is obtained by capturing an image of at least one of patient and wherein the label data is obtained by reflecting a distance in an anterior direction between a corneal apex and a lateral orbital rim of an eye of the at least one of patient.