Artificial Intelligence Algorithms for the Ultrasonographic Periodontal Probe
نویسنده
چکیده
Periodontal disease, commonly known as gum disease, affects millions of Americans. The current method of detecting periodontal disease is painful, invasive, and inaccurate. As an alternative to manual probing, the ultrasonographic periodontal probe is being developed to use RF ultrasound waveforms to measure periodontal pocket depth, which is the main measure of periodontal disease. The methods employed use wavelet transforms and pattern recognition techniques to develop artificial intelligence routines that can automatically detect pocket depth. Results with pattern classification show that as much as 86.6% of the periodontal pocket depths can be predicted within the manual probe’s 1mm tolerance. Applying ultrasound to dentistry in this way1 is useful for long-term flight situations in the space industry.
منابع مشابه
Pattern Classification Techniques for the Ultrasonographic Periodtonal Probe
Periodontal disease, commonly known as gum disease, affects millions of Americans. The current method of detecting periodontal disease is painful, invasive, and inaccurate. As an alternative to manual probing, the ultrasonographic periodontal probe is being developed to use RF ultrasound waveforms to measure periodontal pocket depth, which is the main measure of periodontal disease. The methods...
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