Imagoworks Inc.

Hannah Kim

Youngjun Kim

Jinhyeok Choi

Tae-geun Son

Bonjour Shin

Donguk Kam

An automated registration method of 3D facial scan data and 3D volumetric medical image data using deep learning, includes extracting scan landmarks from the 3D facial scan data using a convolutional neural network, extracting volume landmarks from the 3D volumetric medical image data using the convolutional neural network and operating an initial registration of the 3D facial scan data and the 3D volumetric medical image data using the scan landmarks and the volume landmarks.

Automated registration method of 3D facial scan data and 3D volumetric medical image data using deep learning and computer readable medium having program for performing the method

An automated method for aligning a 3D dental library model to 3D oral scan data includes determining a valid tooth of the 3D oral scan data, extracting scan landmarks of the 3D oral scan data, loading a dental library model corresponding to the valid tooth of the 3D oral scan data, extracting library landmarks of the 3D dental library model, initial-aligning the 3D dental library model to the 3D oral scan data using the scan landmarks and the library landmarks and matching an individual tooth of the 3D dental library model and an individual tooth of the 3D oral scan data.

Automated method for aligning three dimensional dental library model to three dimensional oral scan data and computer readable medium having program for performing the method

An automated method for aligning 3D (three-dimensional) dental data includes extracting landmark points of a CT (computerized tomography) data, extracting landmark points of scan data of a digital impression model, determining an up vector representing a direction of a patient's eyes and nose and identifying left and right of the landmark points of the scan data, extracting a teeth portion of the scan data, searching a source point of the scan data on a spline curve of the CT data to generate a candidate target point group and determining the candidate target point group having a smallest error with the landmark points of the CT data as a final candidate.

Automated method for aligning 3D dental data and computer readable medium having program for performing the method

A method for automated detection of landmarks from 3D medical image data using deep learning according to the present inventive concept, the method includes receiving a 3D volume medical image, generating a 2D intensity value projection image based on the 3D volume medical image, automatically detecting an initial anatomical landmark using a first convolutional neural network based on the 2D intensity value projection image, generating a 3D volume area of interest based on the initial anatomical landmark and automatically detecting a detailed anatomical landmark using a second convolutional neural network different from the first convolutional neural network based on the 3D volume area of interest.

Growing community of inventors

Seoul, South Korea

Hannah Kim