Abstract: Provided are a method of generating an orthodontic treatment plan based on a sequential staging technology, a computing device for performing the same, and a recording medium. A method of generating an orthodontic treatment plan based on the sequential staging technology according to various embodiments of the present disclosure, which is a method performed by a computing device, includes generating a three-dimensional (3D) teeth model including a plurality of individual tooth models generated by individually modeling each of a plurality of teeth of a subject and generating an orthodontic treatment plan for performing stepwise orthodontic treatment on teeth requiring orthodontic treatment among the plurality of teeth using the generated 3D teeth model.

Abstract: Provided is a method of performing registration between a plurality of images of different dimensions. The method may be performed by one or more processors of a computing device, and may include primarily positioning a three-dimensional (3D) image by identifying a first landmark in the 3D image, generating a registration image by registration between the primarily positioned 3D image and a two-dimensional (2D) image, and secondarily positioning the registration image.

Abstract: A method, computing device, and recording medium for providing a solution for establishing orthodontic planning using a 3D tooth model are provided. A method of providing a solution for establishing orthodontic planning using a 3D tooth model by a computing device according to various embodiments of the present invention includes: generating the 3D tooth model including a plurality of individual tooth models generated by individually modeling each of a plurality of teeth for a target; and providing the solution for establishing orthodontic planning based on the generated 3D tooth model.

Abstract: The present invention relates to a method for determining density values for specific tissues of the head and neck based on artificial intelligence. The method of the present invention includes an operation in which a computerized tomography (CT) image obtainer obtains a CT image of the head and neck of a patient from CT apparatuses of a plurality of different manufacturers, an operation in which a voxel image extractor extracts a plurality of voxel images for each density value section from the obtained CT image and merges the extracted plurality of voxel images, and an operation in which an image-of-interest classifier classifies an image of interest by inputting the merged voxel image into an image-of-interest selection model and estimating a position value.

Abstract: The present disclosure relates to a method for detecting a landmark of the head and neck based on artificial intelligence. The method includes an operation of obtaining an original computerized tomography (CT) image of a head and a neck of a patient, an operation of converting the obtained original CT image into a low-resolution CT image, an operation of detecting a first landmark by inputting the low-resolution CT image into a landmark detection model, an operation of detecting a peripheral area based on the detected first landmark of the head and neck, an operation of restoring an original CT image of the detected peripheral area, and an operation of detecting a second landmark by inputting the restored image of the peripheral area into the landmark detection model.

Abstract: Provided is a method of providing a surgery simulation according to various embodiments of the present disclosure to solve the above-described problems. The method is performed by one or more processors of a computing device, and includes generating three-dimensional (3D) modeling data on the basis of a medical image, generating a user interface including the 3D modeling data, and providing the user interface to a user terminal, and generating surgery simulation result data by performing the surgery simulation on the basis of a response to the user interface, the response being received from the user terminal.

Abstract: Provided is a method of performing registration between a plurality of images of different dimensions. The method may be performed by one or more processors of a computing device, and may include primarily positioning a three-dimensional (3D) image by identifying a first landmark in the 3D image, generating a registration image by registration between the primarily positioned 3D image and a two-dimensional (2D) image, and secondarily positioning the registration image.

Abstract: Provided is a face transformation simulation method. The method is performed by one or more processors of a computing device, and includes obtaining three-dimensional (3D) volume data and 3D facial data, generating matching data by matching the 3D volume data and the 3D facial data, generating a user interface including the matching data and providing the user interface to a user terminal, and performing transformation on the matching data on the basis of a response to the user interface, which is received from the user terminal.