Align Technology, Inc.

Auris Health, Inc.

Arevo, Inc.

Auris Surgical Robotics, Inc.

Paren Shah

Andrey Cherkas

Anatoliy Parpara

Alexey Kalinichenko

Shiva Prasad Sambu

Hemant Bheda

Stephan Albert Alexandre Dumothier

Israel Velazquez

Jack Shaw

Ivan Kharpalev

Kwan Ho

Enrique Soltero Borrego

Ben Castricone

Ari Siletz

Systems and methods for performing automated quality control for 3D printed molds for orthodontic aligners are described. A method includes generating a plurality of images of the 3D printed mold for the orthodontic aligner using one or more imaging devices, wherein each image of the plurality of images depicts a distinct region of the 3D printed mold for the orthodontic aligner; processing the plurality of images by a processing device to identify one or more types of manufacturing defects of the 3D printed mold for the orthodontic aligner, wherein for each type of manufacturing defect a probability that an image comprises a defect of that type of manufacturing defect is determined; and classifying, by the processing device, the 3D printed mold for the orthodontic aligner as defective based on identifying the one or more types of manufacturing defects.

Automated quality control for three-dimensional (3D) printed mold for orthodontic aligner

A basket apparatus is described that assists in removing objects from within a patient. The apparatus includes a number of pull wires, each pull wire physically coupled to a different capstan that individually actuates one of the pull wires. The apparatus also includes an outer support shaft itself including a number of channels through which the pull wires traverse. The portions of the pull wires extending out of the outer support shaft form a basket of adjustable size, shape, and position. The pull wires are attached together at a tip located at a distal end of the basket apparatus. By controlling the actuation of the various pull wires, the basket's shape, position size can be manipulated to reposition the basket around an object located within a patient, independent of or in conjunction with motion of the remainder of the apparatus or an associated endoscope.

Basket apparatus

The present disclosure provides methods for generating a three-dimensional object, comprising directing at least one strand material from a source of at least one strand material towards a base. Next, at least a first light beam and a second light beam from a light source is used to subject at least one strand material to heating at one or more locations along at least one strand material. At least a portion of the three-dimensional object may be generated from at least one strand material upon subjecting at least one strand material to heating along one or more locations.

Methods and systems for three-dimensional printing of composite objects

Implementations describe systems and methods for machine based defect detection of three-dimensional (3D) printed objects. A method of one embodiment of the disclosure includes providing a first illumination of a 3D printed object using a first light source arrangement. A plurality of images of the 3D printed object are then generated using one or more imaging devices. Each image may depict a distinct region of the 3D printed object. The plurality of images may then be processed by a processing device using a machine learning model trained to identify one or more types of manufacturing defects of a 3D printing process. The machine learning model may provide a probability that an image contains a manufacturing defect. The processing device may then determine, without user input, whether the 3D printed object contains one or more manufacturing defects based on the results provided by the machine learning model.

Machine based three-dimensional (3D) object defect detection

A method for inspecting a customized orthodontic aligner for manufacturing defects, the customized orthodontic aligner customized for a specific arch of a specific patient and a specific stage of orthodontic treatment, the method including obtaining images of the customized orthodontic aligner; identifying an identifier of the customized orthodontic aligner, determining a digital file based on the identifier, the digital file associated with the customized orthodontic aligner including a digital model of a mold used during manufacture of the customized orthodontic aligner, determining a intended property for the customized orthodontic aligner by digitally manipulating the digital model of the mold, determining an actual property of the customized orthodontic aligner from the images, determining whether there is a manufacturing defect in the customized orthodontic aligner by comparing the intended property with the actual property, outputting an output associated with the determination of whether there is a manufacturing defect.

Aligner image based quality control system

Growing community of inventors

Santa Clara, CA, United States of America

Paren Shah