Artificial intelligence architecture for identification of periodontal features

US11348237B2 · kind B2 · utility

Assignee

• Retrace Labs · US

Inventors

• Vasant Kearney · San Francisco, US
• Ali Sadat · San Francisco, US
• Stephen H. Chan · San Francisco, US
• Hamid Hakmatian · San Francisco, US
• Yash Patel · Palo Alto, US

Key dates

• Filing date: May 15, 2020
• Grant date: May 31, 2022
• Expiry date: Dec 4, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V2201/03
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Dental images are processed according to a first machine learning model to determine teeth labels. The teeth labels and image are concatenated and processed using a second machine learning model to label anatomy including CEJ, JE, GM, and Bone. The anatomy labels, teeth labels, and image are concatenated and processed using a third machine learning model to obtain feature measurements, such as pocket depth and clinical attachment level. The feature measurements, anatomy labels, teeth labels, and image may be concatenated and input to a fourth machine learning model to obtain a diagnosis for a periodontal condition. Feature measurements and/or the diagnosis may be processed according to a diagnosis hierarchy to determine whether a treatment is appropriate. Machine learning models may further be used to reorient, decontaminate, and restore the image prior to processing. Machine learning models may be embodied as CNN, GAN, and cyclic GAN.