Contents & References of Presenting a new method to investigate the treatment process of lesions and tooth bone loss in a period of time
List:
The first chapter: Introduction
1-1- General. 2
1-2- An introduction to dental radiology. 3
1-2-1- Cephalometric radiography 4
1-2-2- Dental radiography digital systems 5
1-2-3- Periapical radiography 7
1-2-4- Panoramic radiography (Panorex) 8
1-2-5- Intraoral cameras 9
1-3- Definition of the problem. 9
1-4- A look at the thesis chapters. 11
1-5- Summary. 12
The second chapter: Research background
2-1- Introduction. 14
2-2- Existing methods for separating and segmenting dental images. 16
2-2-1 Saeed et al.'s method 17
2-2-2- Anil Jin and Heng Chen's method 26
Title
2-2-3- Fang Din and Bak Huai's method 28
2-2-4- Method of Vijayakumari et al. 36
2-3- Available methods for examining and diagnosing dental lesions. 40
2-3-1- methods of examination and treatment of tooth root resorption 40
2-3-2 methods of examination and diagnosis of dental lesions around the end of the root 41
2-3-2-1 Mol and Venn method. 41
2-3-2-2 Jang and Lee method. 44
2-4- Summary. 46
The third chapter: Research method
3-1- Introduction. 48
3-2- Preprocessing and improving the quality of images. 49
3-2-1-Synthetic filter. 52
3-3- Division and separation of teeth 52
3-3-1- Storage mapping histogram 53
3-3-2- Rotation angle estimation: 55
3-4- Identifying the end of the tooth root: 61
3-5- Detection of bone lesions around the root of the tooth: 64
3-6- Summary. 65
Chapter Four: Experiments and results
4-1- Introduction. 67
4-2- Checking the results of the pre-processing stage. 68
Title Page 4-3-4-3-4-3-1- Results and tests of the teeth segmentation stage 73
4-3-2- Evaluation of teeth segmentation stages 76
4-4- The results of the tooth root end detection algorithm: 82
4-5- Assessment and diagnosis of bone lesions at the end of the tooth root. 84
4-6- Summary. 86
The fifth chapter: Conclusions and suggestions
5-1- Conclusions and suggestions for future work 88
List of sources. 90
Source:
[1] root treatment. (n.d.). Retrieved 1 14 2013, from roshd: http://daneshnameh.roshd.ir/mavara/mavara-print.php?page=Darman+Risheh
[2] Medical Engineering Articles (n.d.). Retrieved 12 26 2012, from : http://bmeiaut.salamatblog.ir/1389/05/03/57/
[3] D. Kim, B. Lee, "Quantitative Analysis of Endodontic Treatment for Periapical Lesions in Intraoral Radiographs," 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering, Taichung, Taiwan, pp. 352-355, June 2009.
[4] N.M.R, A. E. (1980). Imaging of intact biological systems. Philos trans R soc lond (biol) , 471-481.
[5] Taylor Z.D., Rahul D., Bennett D. (2012, sep). THz medical imaging: in vivo hydration sensing. IEEE transaction on terahertz science and technology, 1(1).
[6] Townsend, D. W. (2008). Dual-modality imaging: combining anatomy and function. Journal of Nucl Med.
[7] E. Said, D. Nassar, G. Fahmy, and H. Ammar. (2006, June). Teeth segmentation in digitized dental x-ray films using mathematical morphology. IEEE Trans. Inf. Security Forensics, 1, 178–189. [8] R. C. Gonzales, R. E. Woods. (2002). Digital Image Processing. Upper Saddle River: Prentice-Hall. [9] J. Zhou and M. Abdel Mottaleb. (2005, November). A content-based system for human identification based on bitewing dental x-ray images. Pattern Recognition, 38(11), 2132-2142.
[10] A. Jain and H. Chen. (2004, July). Matching of dental x-ray images for human identification. pattern recognitionPattern Recognition, 37(7), 1519-1532. [11] Vo Phong Dinh, Le Bac–Hoai. (2008). Dental radiographs Segmentation Based on Tooth Anatomy. IEEE International Conference on Research, Innovation and Vision for the Future in Computing & Communication Technologies.
[12] Tooth, (n.d.). Retrieved 10 8 2012, from Dr Sharif Weblog: http://doctorsharif.blogfa.com/category/1
[13] B. Vijayakumari, G. UIaganathan, A. Banumath. (2011). An effective shape extraction algorithm for dental radiographs using contour information. international journal of computer science and technology. [14] Levander E, Bajka R, Malmgren O. (1998). Early Radiographic Diagnosis of Apical Root Resorption During Orthodontic Treatment: A Study Of Maxillary Incisors. Eur J Orthod, 57-63. [15] Evelise Ono, et al. (2011, March). Evaluation of simulated external root resorptions with digital radiography and digital subtraction radiography. American journal of orthodontics and dentofacial orthopedics, 324-333. [16] A Mol, P. F. (1991, April). Application of Digital Image Analysis in Dental Radiography for the Description of Periapical Bone Lesions: A Preliminary Study. IEEE transactions on biomedical engineering, 38(4). [17] D. Kim, B. Lee. (2009). Quantitative Analysis of Endodontic Treatment for Periapical Lesions in Intraoral Radiographs; IEEE International Conference on Bioinformatics and Bioengineering, Taichung, Taiwan.352-355.
[18] Goebe, P. M. (2006). Noise estimation and multiresolution reconstruction for dental panoramic X-ray images. Diploma thesis.
[19] Image quality. (n.d.). Retrieved from mpas: http://www.mpas.ir/mri/31-image-quality.html
[20] Homomorphic filtering. (n.d.). Retrieved 6 26 2012 from wikipedia: http://en.wikipedia.org/wiki/Homomorphic_filtering
[21] R. Khanna and W. Shen. (1994). Automated fingerprint identification system (AFIS) benchmarking using the National Institute of Standards and Technology (NIST) special database. in Proc. Inst. Elect. Electron.Eng. 28th Annu. Int. Carnahan Conf., Albuquerque, NM. 188–194.
[22] D. E. Nassar. A prototype automatic dental identification system (ADIS). (2000) M.Sc. dissertation, Dept. Elect. Comput. Eng. West Virginia Univ. Morgantown, Apr. 2001. [23] S. White and M. Pharoah. Oral Radiology Principles and Interpretation, 4th ed. St. Louis, MO: Mosby, 2000.
[24] Yuniarti, A., Zainal Arifin, A., Yudhi Wijaya, A., & Nurul Khotimah, W. (2012). An Age Estimation Method to Panoramic Radiographs from Indonesian Individuals. TELKOMNIKA (Telecommunication, Computing, Electronics and Control), 10(1), 137-146
[25] P. Maragos and R. W. Schafer. (1990) Morphological systems for multidimensional signal processing. Proc. IEEE. 78(4). 690–710
[26] K. Held, E. R. Kops, B. J. Krause, W. M. Wells, and R. Kikinis. (1997, December). Markov random field segmentation of brain MR images. IEEE Trans. Med. Image. 16(6). 878–886
[27] Lin, P. L., Huang, P. Y., & Huang, P. W. (2012). An automatic lesion detection method for dental x-ray images by segmentation using variational level set. In ICMLC (pp. 1821-1825). [28] S. Shiffman, G. D. Rubin, and S. Naples. (2000, November). Medical image segmentation using analysis of isolable-contour maps. IEEE Trans. Med. Image. 19(1). 1064–1074 [29] V. Grau, A. U. J. Mewes, M. Alcaniz, R. Kikinis, and S. K. Warfield. (2004, April). Improved watershed transform for medical image segmentation using prior information. IEEE Trans. Med. Image. 23(4) 447–458. [30] L.G. Brown. (1992). A survey of image registration techniques. ACM Comput. Surveys 24(4). pp325
[31] J.J Charles, L.I. Kuncheva, B. Wells, I.S. Lim. (2006, September). An evaluation measure of image segmentation based on object centers. in: Proc. Of the international conference on image analysis and recognition, Portugal, 18-20, [32] G. Jonasson, G.