DEEP LEARNING FOR TOOTH DETECTION AND EVALUATION

    公开(公告)号:US20190180443A1

    公开(公告)日:2019-06-13

    申请号:US16182452

    申请日:2018-11-06

    Abstract: A machine learning model is trained to define bounding shapes around teeth in images. The machine learning model is trained by receiving a training dataset comprising a plurality of images, each image of the plurality of images comprising a face and a provided bounding shape around teeth in the image. The training dataset is input into an untrained machine learning model. The untrained machine learning model is trained based on the training dataset to generate a trained machine learning model that defines bounding shapes around teeth in images, wherein for an input image the trained machine learning model is to output a mask that defines a bounding shape around teeth of the input image, wherein the mask indicates, for each pixel of the input image, whether that pixel is inside of a defined bounding shape or is outside of the defined bounding shape.

    Tooth segmentation based on anatomical edge information

    公开(公告)号:US12144701B2

    公开(公告)日:2024-11-19

    申请号:US18446445

    申请日:2023-08-08

    Abstract: Provided herein are orthodontic systems and methods for automatically segmenting a person's teeth. Systems, methods and processes are provided to properly segment the teeth of a person's teeth from an image of the person's face showing at least some of the person's teeth (e.g., dental arch). Methods and systems are provided to automatically detect dental edges after a dental scan. Also described herein are methods and systems for generating a simulated image of the person's face from the final segmentation of the person's teeth in which the segmented teeth have been moved from their original position, including a new position based on an orthodontic treatment plan.

Patent Agency Ranking