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: Computer-implemented methods and systems for designing oral appliances. These methods and systems may include receiving patient data and a treatment plan (including a proposed one or more dental appliances), and determining, using the patient data and the treatment plan, an improved appliance design for treating the patient. These methods and systems may include evaluating the appliance design based on simulation and finalizing the appliance design based on the evaluation.

Abstract: A method of automatically registering landmarks in a 3-dimensional (3D) medical image includes obtaining a 3D image; determining a set of search points based on a statistical atlas attached to a bounding box corresponding to a part of the 3D image; extracting features of the determined set of search points; forming a set of candidates for a landmark based on the extracted features; filtering the candidates and outputting remaining candidates among the candidates based on the filtering; and outputting a final position of the landmark based on one of the remaining candidates.

Abstract: A method of automatically registering landmarks in a 3-dimensional (3D) medical image includes obtaining a 3D image; determining a set of search points based on a statistical atlas attached to a bounding box corresponding to a part of the 3D image; extracting features of the determined set of search points; forming a set of candidates for a landmark based on the extracted features; filtering the candidates and outputting remaining candidates among the candidates based on the filtering; and outputting a final position of the landmark based on one of the remaining candidates.

Abstract: A method of automatic planning of a view in a 3D image of a brain includes A method of automatic planning a view in a three-dimensional (3D) image of a brain includes selecting a plurality of axial working sections and a plurality of coronal working sections in the 3D scout image; constructing at least one mid-sagittal plane of the brain based on a set of axial reference lines and a set of coronal reference lines obtained from the selected plurality of axial working sections and the selected plurality of coronal working sections, respectively; detecting at least one landmark that is an anatomical point in the at least one mid-sagittal plane; creating a first reference line based on the at least one landmark detected in the at least one mid-sagittal plane; and planning a scan in an orientation based on the at least one mid-sagittal plane and the first reference line.

Abstract: Provided is medical equipment and a technique for analyzing medical images. A method for automatically planning views in three-dimensional (3D) medical images includes: estimating a statistical model indicating positions of anatomical points, the statistical model having parameters calculated by minimizing energy of a loss function; training an anatomical point detector to detect the plurality of anatomical points by using the estimated statistical model; acquiring a 3D image having a region of interest; detecting a set of candidates of the anatomical points in the 3D image; searching the set of candidates for an optimal configuration corresponding to the plurality of anatomical points; and forming a view plane based on the optimal configuration found by the searching.

Abstract: A method of automatic planning of a view in a 3D image of a brain includes A method of automatic planning a view in a three-dimensional (3D) image of a brain includes selecting a plurality of axial working sections and a plurality of coronal working sections in the 3D scout image; constructing at least one mid-sagittal plane of the brain based on a set of axial reference lines and a set of coronal reference lines obtained from the selected plurality of axial working sections and the selected plurality of coronal working sections, respectively; detecting at least one landmark that is an anatomical point in the at least one mid-sagittal plane; creating a first reference line based on the at least one landmark detected in the at least one mid-sagittal plane; and planning a scan in an orientation based on the at least one mid-sagittal plane and the first reference line.

Abstract: Provided is medical equipment and a technique for analyzing medical images. A method for automatically planning views in three-dimensional (3D) medical images includes: estimating a statistical model indicating positions of anatomical points, the statistical model having parameters calculated by minimizing energy of a loss function; training an anatomical point detector to detect the plurality of anatomical points by using the estimated statistical model; acquiring a 3D image having a region of interest; detecting a set of candidates of the anatomical points in the 3D image; searching the set of candidates for an optimal configuration corresponding to the plurality of anatomical points; and forming a view plane based on the optimal configuration found by the searching.