Abstract
Diagnosis of caries is a difficult process in the clinical setting, because of the obvious reasons like edge line in the Approximal surfaces is not so clear and also the complicated setting of pits and fissures in the Occlusal surface. Due to this, dependency on the expert advice of doctor increases which changes, with difference in opinion of different doctors. This indirectly affects the Sensitivity and Specificity of the disease in the radiographs used. The goal of this work is to study digital radiographs in this case we are using IOPA for dental caries. Then find out which image is having caries, whether it is visible or not, if yes than what amount of caries it is comprised of, if no than what is the reason behind it. Now to find the visibility we have preprocessed the image using an algorithm which de noises the image and also enhances the image quality, maintaining its medical standards. Also, we have used artificial intelligence to initially diagnose the carious legions by detecting those areas where caries generally occurs like the approximal surface and occlusal surface of the tooth. This approach of diagnosing the carious legions has opened gates for diagnosis of some others diseases also.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rafael, C.G., Richard, E.W.: Digital Image Processing, 3rd edn. Pearson Education, 2013
Rafael, C.G., Richard E.W.: Digital Image Processing Using Matlab, 2nd edn. Pearson Education, 2013
Wolberg, G.: Digital Image Wrapping, IEEE Computer Society Press, 1999
Singh, H.V.: Information Hiding Techniques for Image Covers, LAP LAMBERT Academic Publishing GmbH & Co. KG, Ddudweiler Landstr. 99, 66123 Saarbrücken, Germany, 2010
Pratt, W.K.: Digital Image Processing, 3rd edn. Wiley & Sons, Inclusive, New Jersey (2001)
Singh, H.V., Rai A.: SVM Based Robust Watermarking For Enhanced Medical Image Security, Computers and Electrical Engineering, Elsevier Publication, Amsterdam, 2009
Rasche, K., Geist, R., Westall, J.: Re-coloring images for gamuts of lower dimension. Comput. Graph. Forum (Proc. Euro Graph.) 24, 423–432 (2005)
Strickland, R.N., Kim, C.S., McDonnell, W.F.: Digital colour image enhancement based on the saturation component. Opt. Eng. 26, 609–616 (1987)
Cheng, S.-C. Hsia, S.-C.: Fast algorithms for colour image processing by principal component analysis. J. V. Commun. Image Represent. 24, 184–203 (2003)
Hanbury, A.G., Serra, J.: Morphological operators on the unit circle. IEEE Trans. Image Proc. 10, 842–1850, (2001)
Chellappa, R.: Digital Image Processing, 2nd edn, IEEE Computer Society Press, 1992
Uprichard, K.K., Potter, B.J., Russel, C.M., Schafer, TE., Adair, S., Weller, R.N.: Comparison of direct digital and conventional radiography for the detection of proximal surface caries in the mixed dentition. Am. Acad. of Padiatr. Dent. 22(1), 10–15 (2000)
Wenzel, A.: Digital radiography and caries diagnosis. Dentomaxillofacial Radiol. 27, 3–11 (1998)
MATLAB and Image Processing Toolbox Release.: The MathWorks, Inc., Natick, Massachusetts, United States (2015a)
White, S.C., Yoon, DC.: Comparative performance of digital and conventional images for detecting proximal surface caries. Dentomaxillofacial Radiol. 26, 32–38 (1997)
Tyndall, DA., Ludlow, JB., Platin, E., Nair, M.: A comparison of Kodak Ektaspeed Plus film and the Siemans Sidexis digital imaging system for caries detection using receiver operating characteristic analysis. Oral Surg. Oral Med. Oral Pathol. 85, 113–118 (1998)
Price, C., Ergul, N.: A comparison of a film-based and a direct digital dental radiographic system using a proximal caries model. Dentomaxillofac Radiol. 26, 45–52 (1997)
Naitoh, M., Yuasa, H., Yoyama, M., Shiozima, M., Nakemerra, M., Ushida, M., Iida, H., Hayashi, M., Ariji, E.: Observer agreement in the detection of proximal caries with direct digital intraoral radiography. Oral Surg. Oral Med. Oral Pathol. 85, 107–112 (1998)
Selwitz, R.H., Ismail, A.I., Pitts, N.B.: Dental caries. The Lancet 369(9555), 51–59 Jan. (2007)
Nielsen, L.L., Hoernoe, M., Wenzel, A.: Radiographic detection of cavitation in approximal surfaces of primary teeth using a digital storage phosphor system and conventional film, and the relationship between cavitation and radiographic lesion depth: an in vitro study. Int. J. Paediatr. Dent. 6, 167–172 (1996)
Metz, C.E.: Basic principles of ROC analysis. Semin. Nucl. Med. 8, 283–298 (1978)
Hanley, J.A., McNeil, B.J.: A method of comparing the areas under the receiver operating characteristics curves derived from the same cases. Dentomaxillofacial Radiol. 148, 839–843 (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Singh, H.V., Agarwal, R. (2018). Diagnosis of Carious Legions Using Digital Processing of Dental Radiographs. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_74
Download citation
DOI: https://doi.org/10.1007/978-3-319-71767-8_74
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-71766-1
Online ISBN: 978-3-319-71767-8
eBook Packages: EngineeringEngineering (R0)