Abstract: Provided is a method for generating an orthodontic teeth alignment shape for the orthodontic treatment of a patient. According to the present invention, there is provided a method for generating an orthodontic teeth alignment shape, the method including the steps of: acquiring a patient's teeth shape information; extracting specific points of respective teeth within a given range of at least one of the patient's upper and lower jaws, based on the acquired teeth shape information; comparing the patient's arch form produced by connecting the specific points to one another with a plurality of standard arch forms stored in a database; selecting the standard arch form that is most similar to the patient's arch form from the plurality of standard arch forms stored in the database, based on the comparison result; and generating the orthodontic teeth alignment shape based on the selected standard teeth alignment form.

Abstract: Provided is a computing device for supporting medical image analysis. The computing device may include: at least one or more memories for storing a program composed of one or more modules for performing medical image analysis; a communication unit for acquiring a medical image and a facial image for a patient's head; and at least one processor for detecting a plurality of feature points from the facial image through a feature point detection module performing artificial neural network-based machine learning to thus superimpose the medical image and the facial image on top of each other with respect to a plurality of first feature points displayed on the medical image and a plurality of second feature points as at least some of the feature points detected from the facial image, wherein the first feature points are anatomical reference points indicating relative positions of at least one of facial skeleton, teeth, and facial contour.

Abstract: Provided is a method of analyzing a dental image for a correction diagnosis and an apparatus using the same. The method includes the steps of obtaining a dental image of an examinee and detecting at least some of a plurality of landmarks for a correction diagnosis in the dental image using a landmark detection module, wherein the landmark is an anatomical reference point indicative of a relative position of at least one of a facial skeleton, a tooth and a face contour necessary for t correction diagnosis, and the landmark detection module may include a machine learning module based on an artificial neural network.