3Shape A/s

Newton2 Aps

Henrik Öjelund

Rune Fisker

Karl-Josef Hollenbeck

Mike Van Der Poel

Arish A Qazi

Rasmus Kjær

Rasmus Kjaer

Thomas Sangild Sørensen

Sami Brandt

Morten Boll

Jens Peter Holme

Michael Vinther

Anders Gaarde

Kristian Evers Hansen

Tais Clausen

Nikolaj Deichmann

David Fischer

Asger Vejen Hoedt

Stefan Elmsted Jensen

Thomas Allin Højgaard

Erik Ask

Zenjie Li

Marek Krzysztof Misztal

Rasmus KJÆR

Christopher Simon Edwards

Alfredo Chávez Plascencia

A scanner includes a camera, a light source for generating a probe light incorporating a spatial pattern, an optical system for transmitting the probe light towards the object and for transmitting at least a part of the light returned from the object to the camera, a focus element within the optical system for varying a position of a focus plane of the spatial pattern on the object, unit for obtaining at least one image from said array of sensor elements, unit for evaluating a correlation measure at each focus plane position between at least one image pixel and a weight function, a processor for determining the in-focus position(s) of each of a plurality of image pixels for a range of focus plane positions, or each of a plurality of groups of image pixels for a range of focus plane positions, and transforming in-focus data into 3D real world coordinates.

Intraoral scanning apparatus

A method for generating a digital 3D representation of at least a part of an intraoral cavity, the method including recording a plurality of views containing surface data representing at least the geometry of surface points of the part of the intraoral cavity using an intraoral scanner; determining a weight for each surface point at least partly based on scores that are measures of belief of that surface point representing a particular type of surface; executing a stitching algorithm that performs weighted stitching of the surface points in said plurality of views to generate the digital 3D representation based on the determined weights; wherein the scores for the surface points are found by at least one score-finding algorithm that takes as input at least the geometry part of the surface data for that surface point and surface data for points in a neighbourhood of that surface point.

Intraoral scanning with surface differentiation

Disclosed is a method of storing information in a mesh, including tessellating a plurality of input patches of the mesh, serializing vertices of the tessellated input patches, calculating a value for each vertex, serializing the values according to the serialization of the vertices; and storing the serialized values.

Storage, rendering, and display of information of meshes through tessellation with serialized values

A computer-implemented method of generating a dental model based on an objective function output, including creating an objective function including at least one quality estimation function which trains at least one machine learning method that generates quality estimation output, and an objective function output is the output of the objective function providing a model as an input data to the objective function and generating model-related objective function output; and modifying the model based on the model-related objective function output to transform the model to a generated model, wherein the generated model is the dental model.

Method for generating dental models based on an objective function

Detecting a movable object in a location includes providing a first 3D representation of at least part of a surface; providing a second 3D representation of at least part of the surface; determining for the first 3D representation a first excluded volume in space where no surface can be present; determining for the second 3D representation a second excluded volume in space where no surface can be present; if a portion of the surface in the first 3D representation is located in space in the second excluded volume, the portion of the surface in the first 3D representation is disregarded in the generation of the virtual 3D model, and/or if a portion of the surface in the second 3D representation is located in space in the first excluded volume, the portion of the surface in the second 3D representation is disregarded in the generation of the virtual 3D model.

Detection of a movable object when 3D scanning a rigid object

Disclosed is a method for compensating for motion blur when performing a 3D scanning of at least a part of an object by means of a 3D scanner, where the motion blur occurs because the scanner and the object are moved relative to each other while the scanning is performed, and where the motion blur compensation comprises: &#x2014;determining whether there is a relative motion between the scanner and the object during the acquisition of the sequence of focus plane images; &#x2014;if a relative motion is determined, performing a motion compensation based on the determined motion; and &#x2014;generating a 3D surface from the sequence of focus plane images.

Motion blur compensation

A method for improving the accuracy of a digital medical model of a part of a patient, the method includes obtaining a set of at least 2 medical images of the patient, where an element including a predefined geometry and/or predefined information was attached to the patient during the recording of the medical images; obtaining at least 2 tracking images taken with at least one camera having a known positional relationship relative to the medical imaging device, the tracking images depicting at least part of the element; determining any movement of the element between acquisition of the at least 2 tracking images; and generating the digital medical model from the acquired medical images, wherein the determined movement of the element is used to compensate for any movement of the patient between the acquisition of the medical images.

System and method for increasing the accuracy of a medical imaging device

Growing community of inventors

Lyngby, Denmark

Henrik Öjelund