Narrative
Manchester Imaging Limited is a dental diagnostic software spinout from the University of Manchester. The company software aims to assist dentists in detecting early tooth decay, before a filling is needed, empowering patients to look after their teeth more effectively and saving money for insurance companies and governments by reducing the need for dental restorations and repairs. Detecting early-stage enamel caries has the big advantage of avoiding the need for fillings, which are necessary when decay is identified at a later, more advanced stage. However, detecting early-stage enamel caries can be difficult and time consuming by visual inspection alone. The company's first product AssistDent® was launched in 2019 and uses artificial intelligence to help community dentists identify decay at an early stage, when it can be reversed – for instance, by applying fluoride varnishes –removing the need for fillings later.Impact date | 2014 |
---|---|
Category of impact | Health and wellbeing, Technological, Economic |
Impact level | Benefit |
Research Beacons, Institutes and Platforms
- Digital Futures
- Institute for Data Science and AI
Documents & Links
Related content
-
Research output
-
Improving the detection of osteoporosis from dental radiographs using Active Appearance Models
Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review
-
Changes in mandibular cortical width measurements with age in men and women
Research output: Contribution to journal › Article › peer-review
-
The role of the dental surgeon in detecting osteoporosis: The OSTEODENT study
Research output: Contribution to journal › Article › peer-review
-
The ADEPT Study, A Comparative Study of Dentists’ Ability to Detect Enamel-only Proximal Caries in Bitewing Radiographs With and Without the use of AssistDent® Artificial Intelligence Software
Research output: Contribution to journal › Article › peer-review
-
Image texture in dental panoramic radiographs as a potential biomarker of osteoporosis
Research output: Contribution to journal › Article › peer-review