ARTIFICIAL INTELLIGENCE IN DENTISTRY
ARTIFICIAL INTELLIGENCE FOR
BETTER DENTAL DIAGNOSTICS
Keep up to date on the latest developments!
- Fast (2-3 second per tooth)
- Zero Radiation
- Real-Time Diagnosis
- Long-Term Trend Analysis
How QPD Technology Combined with Artificial
Intelligence Works to Diagnose Cracks
The InnerView™ ai Diagnostic System uses Quantitative Percussion Diagnostics “QPD™” a light, painless percussive tapping on the tooth. Within 2.5 milliseconds per tap, rich data is captured by sensors on the tip of the handpiece. This data is then processed in real time through our propriety algorithm to detect specific crack type, including
InnerView™ System Patient Diagnostic Screen
- A force sensor triggers activation once the tip is applied to a tooth or implant. Once activated, a light percussive tap is applied to the tooth or implant, which takes only 2.5 milliseconds.
- A single tooth can be tested in 3 seconds, the entire mouth in less than 3 minutes.
- QPD™ generates measurable energy feedback, which is captured by the data collection handpiece.
- The rich data captured is then fed into proprietary Artificial Intelligence algorithms. Results are displayed, on screen, in real time.
InnerView™ System Disposable Tip
InnerView™ is designed for maximum infection control. To avoid issues with cross contamination, InnerView™ requires a fresh, single-use, Disposable Tip to be attached to the tip of the handpiece prior to each new procedure.
InnerView™ System Smart Chip Technology
When the Disposable Tip, with embedded security chip are placed on the device, a “challenge and response” test is conducted via the software. After the tip has been verified as new and valid, it is immediately designated for this patient only. InnerView™ can be used for one-hour, that begins at the start of each procedure.
Combining Artificial Intelligence with Quantitative Percussion Diagnostics (QPD) to Detect Cracks & Failing Restorations.
InnerView™ is a breakthrough system that employs Quantitative Percussion Diagnostics “QPD™” to detect cracks, including failing restorations, in teeth.
The mechanism of QPD™ is a light, painless percussive tapping force applied to the tooth or implant. Within just 2.5 milliseconds per tap, incredibly rich data is generated which is then processed through proprietary algorithms to detect specific crack types.
Within seconds, results are displayed on screen with an easy-to-read patient diagnostic screen.
Dentists Upload Data Using InnerView™ Software
Massive amounts of HIPAA compliant data is collected via our data collection handpiece which is uploaded to InnerView™’s Cloud server. Trends are immediately analyzed and correlated to critical damage including cracks and restorations. Over time, and as more and more data is collected, the diagnostic capability will be continuously enhanced.
Background & Leadership
Robert Hayman, CEO of Perimetrics, LLC and prior co-Founder and former CEO/Chairman of Discus Dental, one of the largest and most successful direct dental manufacturers, is joined by Dennis Quan, Ph.D in Computer Science from MIT and former CTO for IBM’S High Performance On Demand Solutions, to lead the company’s global introduction. The company was formed by James Earthman, Ph.D., an expert in percussion technology and Cherilyn Sheets, DDS., a world renowned prosthodontist, lecturer and author. InnerViewTM is scheduled to launch in April 2021.
Chief Executive Officer &
Chairman of the Board
- Co-Founder & former CEO/Chairman, Discus Dental, Inc.
- #1 global direct dental manufacturer – from 1993 startup to $170 million
- Sold to Philips in 2010
- Inventor & Co-Founder Perimetrics, LLC
- Internationally renowned educator, clinician, lecturer & author
- Clinical Professor of Restorative Dentistry, USC
JIM EARTHMAN, PHD
Chief Science Officer &
- Co-Inventor & Co-Founder Perimetrics, LLC.
- Professor: Dept. of Chemical Engineering & Materials Science, The Graduate Division, UC Irvine
- Associate Dean of Professional Development, University of California at Irvine
Chief Technology Officer
- 20+ years of experience in enterprise IT, healthcare/life sciences & large scale data analytics/artificial intelligence.
- Former IBM VP/Chief Technology Officer – led IBM’s entry into Cloud Computing
- Ph.D. Computer Science from MIT (AI Laboratory)