Abstract
Manual pocket depth probing has been widely used as a retrospective diagnosis method in periodontics. However, numerous studies have questioned its ability to accurately measure the anatomic pocket depth. In this paper, an ultrasonic periodontal probing method is described, which involves using a hollow water-filled probe to focus a narrow beam of ultrasound energy into and out of the periodontal pocket, followed by automatic processing of pulse-echo signals to obtain the periodontal pocket depth. The signal processing algorithm consists of three steps: peak detection/characterization, peak classification, and peak identification. A dynamic wavelet fingerprint (DWFP) technique is first applied to detect suspected scatterers in the A-scan signal and generate a two-dimensional black and white pattern to characterize the local transient signal corresponding to each scatterer. These DWFP patterns are then classified by a two-dimensional FFT procedure and mapped to an inclination index curve. The location of the pocket bottom was identified as the third broad peak in the inclination index curve. The algorithm is tested on full-mouth probing data from two sequential visits of 14 patients. Its performance is evaluated by comparing ultrasonic probing results with that of full-mouth manual probing at the same sites, which is taken as the "gold standard."
Highlights
Most adults have a mild form of periodontal disease, while over 20 percent of older Americans have severe periodontal disease [1, 2, 3]
Future work is planned that should answer that and related questions definitively, via dog models as well as human testing where the gold standard is provided via ultrasonic scanning just prior to flap surgery or en bloc surgery followed by histological sectioning
After the location of the bottom of the periodontal pocket is estimated as above, the pocket depth is calculated as the product of the time delay from the probe tip and the speed of ultrasound in water (1.5 mm/μs), divided by two
Summary
Most adults have a mild form of periodontal disease, while over 20 percent of older Americans have severe periodontal disease [1, 2, 3]. As an initial effort to automate interpretation of the echoes, a time-domain procedure was developed to simplify the waveforms and infer the depth of the periodontal pocket [44, 45, 46] This procedure used a slope-detection algorithm to pick peaks in the A-scan signal, followed by smoothing and averaging operations to eliminate small random variations. To take advantage of this potential of the WT, a dynamic wavelet fingerprint technique [57] was adapted to develop a signal processing algorithm for the ultrasonic periodontal probe In this approach, potential scatterers are first detected by picking peaks in the scale-averaged power (SAP) curve.
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