Thyroscope Inc.

Kyubo Shin

Jongchan Kim

Jaemin Park

Yoon Won Tak

Hwi Yeon Kim

Eun Yeong Sim

A method of monitoring an overall thyroid ophthalmopathy treatment includes requesting a user device to take a facial image and enter a questionnaire survey content according to treatment monitoring cycle; obtaining the facial image and the questionnaire survey content from the user device; obtaining, using the facial image and the questionnaire survey content obtained from the user device, a personalized estimate of the user corresponding to exophthalmos information, CAS (Clinical Activity Score) information, and diplopia information among an indicator proven at an approval stage of the medicine; and displaying, which comprises visualizing the personalized estimate of the user in a time-series order from the time the user started administering the medicine on the user device.

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

A method of obtaining user information to analyze a Clinical Activity Score (CAS) of a user is provided. The method includes providing a guidance on a photographing device to indicate a proper position of at least one eye of the user, obtaining a facial image of the user in response to satisfying predetermined conditions. The facial image comprises at least one eye of the user. The predetermined conditions includes 1) whether a position of at least one eye is on a predetermined region, 2) whether a degree of rotation of a face of the user is within a predetermined range, 3) whether a degree of the user's smile is the same or less than a first predetermined value, and 4) whether a degree of ambient brightness is the same or less than a second predetermined value. The method further includes outputting inquiries on the photographing device, and obtaining user input.

Method and photographing device for acquiring side image for ocular proptosis degree analysis, and recording medium therefor

According to the present application, a computer-implemented method of predicting thyroid eye disease is disclosed. The method comprising: preparing a conjunctival hyperemia prediction model, a conjunctival edema prediction model, a lacrimal edema prediction model, an eyelid redness prediction model, and an eyelid edema prediction model, obtaining a facial image of an object, obtaining a first processed image and a second processed image from the facial image, wherein the first processed image is different from the second processed image, obtaining predicted values for each of a conjunctival hyperemia, a conjunctival edema and a lacrimal edema by applying the first processed image to the conjunctival hyperemia prediction model, the conjunctival edema prediction model, and the lacrimal edema prediction model, and obtaining predicted values for each of an eyelid redness and an eyelid edema by applying the second processed image to the eyelid redness prediction model and the eyelid edema prediction model.

Method for hospital visit guidance for medical treatment for active thyroid eye disease, and system for performing same

Provided is a diagnostic system including: a user terminal configured to take an image; and a server configured to obtain diagnosis assistance information on the basis of the image. The user terminal is configured to obtain a first photographing parameter, determine whether a pre-stored condition is satisfied, and transmit the first photographing parameter and a captured image to the server when it is determined that the pre-stored condition is satisfied. The server is configured to obtain a first verification parameter, determine whether to use the captured image as a diagnostic image which includes comparing the first verification parameter with the first photographing parameter, and obtain the diagnosis assistance information by using the diagnostic image when it is determined to use the captured image as the diagnostic image.

Image verification method, diagnostic system performing same, and computer-readable recording medium having the method recorded thereon

According to the present application, provided is a computer-implemented method of predicting a clinical activity score for conjunctival hyperemia. The method described in the present application includes: training a conjunctival hyperemia prediction model using a training set; acquiring a first image include at least one eye of a subject and an outer region of an outline of the at least one eye; outputting, by the conjunctival hyperemia prediction model executing on a processor, a first predicted value for a conjunctival hyperemia, a first predicted value for the conjunctival edema, a first predicted value for an eyelid redness, a first predicted value for an eyelid edema, and a first predicted value for a lacrimal edema; and generating a score for the conjunctival hyperemia based on the selected first predicted value for a conjunctival hyperemia.

The present application relates to a method of acquiring a side image for analyzing the degree of ocular proptosis. According to an embodiment, an image acquisition method is provided which is including: acquiring a front image of the subject's face while guidance is given to satisfy a first photographing condition; generating panorama guidance on the basis of position information of a first point and a second point extracted from the front image; providing guidance on movement of a photographing device to acquire a preview image corresponding to the panorama guidance; and acquiring a side image of the subject's face while guidance is given to satisfy a second photographing condition. The first captured image shows iris areas of the subject, and the second captured image shows an outer canthus and a cornea of one of the subject's eyes.

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Ulsan, South Korea

Kyubo Shin