Wavelet representations for monitoring changes in teeth imaged with digital imaging fiber-optic transillumination

Digital imaging fiber-optic transillumination (DIFOTI) is a novel method to detect and monitor dental caries, using light, a charge-coupled device (CCD) camera, and computer-controlled image acquisition. The advantages of DIFOTI over radiography include: no ionizing radiation, no film, real-time diagnosis, and higher sensitivity in detection of early lesions not apparent to X-ray, as demonstrated in vitro. Here, we present a method of processing DIFOTI images, acquired at different times, for monitoring changes. Of central importance to this application is pattern matching of image frames that is invariant to translation and rotation of a tooth, relative to the field of view of the imaging camera, and that is robust to changes in illumination source intensity. Our method employs: (1) wavelet modulus maxima representations for segmentation of teeth images; (2) first and second moments of gray level representations of DIFOTI images in the spatial domain, to estimate tooth location and orientation; and (3) multiresolution wavelet magnitude representations for quantitative monitoring. Even with illumination source intensity variation, it is demonstrated in vitro that such wavelet representations can facilitate detection of simulated clinical changes in light transmission that cannot be detected in the spatial domain.

[1]  J. T. ten Bosch,et al.  Propagation of light through human dental enamel and dentine. , 1995, Caries research.

[2]  Thomas W. Parks,et al.  A translation-invariant wavelet representation algorithm with applications , 1996, IEEE Trans. Signal Process..

[3]  E. Bronkhorst,et al.  Performance of some diagnostic systems in examinations for small occlusal carious lesions. , 1992, Caries research.

[4]  S. Creanor,et al.  Comparison of fibre optic transillumination with clinical and radiographic caries diagnosis. , 1987, Community dentistry and oral epidemiology.

[5]  Michael F. Cohen,et al.  Course notes: Wavelets and their applications in computer graphics , 1995 .

[6]  J J ten Bosch,et al.  Optical monitor of in vitro caries. A comparison with chemical and microradiographic determination of mineral loss in early lesions. , 1984, Caries research.

[7]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  J. Friedman,et al.  Transillumination of the oral cavity with use of fiber optics. , 1970, Journal of the American Dental Association.

[9]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Stéphane Mallat,et al.  Singularity detection and processing with wavelets , 1992, IEEE Trans. Inf. Theory.

[11]  Dennis M. Healy,et al.  Wavelet transform domain filters: a spatially selective noise filtration technique , 1994, IEEE Trans. Image Process..

[12]  J. T. ten Bosch,et al.  Optical quantitation and radiographic diagnosis of incipient approximal caries lesions. , 1991, Caries research.

[13]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  J Driller,et al.  Assessment of dental caries with Digital Imaging Fiber-Optic TransIllumination (DIFOTI): in vitro study. , 1997, Caries research.

[15]  J. T. ten Bosch,et al.  Regression of white spot enamel lesions. A new optical method for quantitative longitudinal evaluation in vivo. , 1994, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.

[16]  J. Featherstone,et al.  Nature of light scattering in dental enamel and dentin at visible and near-infrared wavelengths. , 1995, Applied optics.

[17]  A. Wenzel New caries diagnostic methods. , 1993, Journal of dental education.

[18]  J. T. ten Bosch,et al.  Regression of white spot enamel lesions. A new optical method for quantitative longitudinal evaluation in vivo. , 1994, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.

[19]  Berthold K. P. Horn Robot vision , 1986, MIT electrical engineering and computer science series.

[20]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[21]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[22]  John W. Woods,et al.  Handbook of visual communications , 1995 .

[23]  R A Groenhuis,et al.  HeNe-Laser Light Scattering by Human Dental Enamel , 1995, Journal of dental research.

[24]  W. Fleischhacker,et al.  A multicenter double-blind study of three different doses of the new cAMP-phosphodiesterase inhibitor rolipram in patients with major depressive disorder. , 1992, Neuropsychobiology.

[25]  Dennis M. Healy,et al.  Contrast enhancement of medical images using multiscale edge representation , 1994, Defense, Security, and Sensing.

[26]  J. M. Cate,et al.  TOOTH ENAMEL REMINERALIZATION , 1981 .