Abstract: Methods, apparatuses, and systems are disclosed for determining accurate tooth root apices from two-dimensional panoramic radiograph data and/or three-dimensional intraoral scan data. In some variations, one or more deep learning networks may be trained to determine coordinates of tooth root apices based on training data that may include cone beam computer tomography tooth data and corresponding two-dimensional panoramic radiograph data and three-dimensional intraoral scan data.

Abstract: Provided herein are systems and methods for automatically segmenting a 3D model of a patient's teeth. A patient's dentition may be scanned with a 3D scanning system, such as CT, CBCT, or MRI. The 3D scan data may be automatically segmented with one or more neural networks. The segmented 3D scan can be incorporated into a dental treatment plan.

Abstract: Apparatuses and computer-implemented methods for compression and extraction of three-dimensional (3D) volumetric imaging data, including in particular medical and dental imaging data, that may receive the 3D volumetric image data and preparing compressed 3D volumetric image data for compression by analyzing a relevant region of the 3D volumetric image data. The method may further include compressing, into compressed 3D volumetric image data, the pre-processed static 3D volumetric image data using a video compression scheme. Various other methods, systems, and computer-readable media are also disclosed.