» Articles » PMID: 20033505

Classification and Numbering of Teeth in Multi-slice CT Images Using Wavelet-Fourier Descriptor

Overview
Publisher Springer
Date 2009 Dec 25
PMID 20033505
Citations 13
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: Teeth arrangement is essential in face ergonomics and healthiness. In addition, they play key roles in forensic medicine. Various computer-assisted procedures for medical application in quantitative dentistry require automatic classification and numbering of teeth in dental images.

Method: In this paper, we propose a multi-stage technique to classify teeth in multi-slice CT (MSCT) images. The proposed algorithm consists of the following three stages: segmentation, feature extraction and classification. We segment the teeth by employing several techniques including Otsu thresholding, morphological operations, panoramic re-sampling and variational level set. In the feature extraction stage, we follow a multi-resolution approach utilizing wavelet-Fourier descriptor (WFD) together with a centroid distance signature. We compute the feature vector of each tooth by employing the slice associated with largest tooth tissues. The feature vectors are employed for classification in the third stage. We perform teeth classification by a conventional supervised classifier. We employ a feed- forward neural network classifier to discriminate different teeth from each other.

Results: The performance of the proposed method was evaluated in the presence of 30 different MSCT data sets including 804 teeth. We compare classification results of the WFD technique with Fourier descriptor (FD) and wavelet descriptor (WD) techniques. We also investigate the invariance properties of the WFD technique. Experimental results reveal the effectiveness of the proposed method.

Conclusion: We provided an integrated solution for teeth classification in multi-slice CT datasets. In this regard, suggested segmentation technique was successful to separate teeth from each other. The employed WFD approach was successful to discriminate and numbering of the teeth in the presence of missing teeth. The solution is independent of anatomical information such as knowing the sequence of teeth and the location of each tooth in the jaw.

Citing Articles

Mapping the Use of Artificial Intelligence-Based Image Analysis for Clinical Decision-Making in Dentistry: A Scoping Review.

Chen W, Dhawan M, Liu J, Ing D, Mehta K, Tran D Clin Exp Dent Res. 2024; 10(6):e70035.

PMID: 39600121 PMC: 11599430. DOI: 10.1002/cre2.70035.


[Tooth segmentation and identification on cone-beam computed tomography with convolutional neural network based on spatial embedding information].

Bo S, Gao C Beijing Da Xue Xue Bao Yi Xue Ban. 2024; 56(4):735-740.

PMID: 39041573 PMC: 11284471.


Deep learning for tooth identification and enumeration in panoramic radiographs.

Sadr S, Mohammad-Rahimi H, Ghorbanimehr M, Rokhshad R, Abbasi Z, Soltani P Dent Res J (Isfahan). 2024; 20:116.

PMID: 38169618 PMC: 10758389.


Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs.

Orhan K, Aktuna Belgin C, Manulis D, Golitsyna M, Bayrak S, Aksoy S Imaging Sci Dent. 2023; 53(3):199-208.

PMID: 37799743 PMC: 10548159. DOI: 10.5624/isd.20230109.


Detecting missing teeth on PMCT using statistical shape modeling.

Rahbani D, Fliss B, Ebert L, Bjelopavlovic M Forensic Sci Med Pathol. 2023; 20(1):23-31.

PMID: 36892806 PMC: 10944413. DOI: 10.1007/s12024-023-00590-w.


References
1.
Scarfe W, Farman A, Sukovic P . Clinical applications of cone-beam computed tomography in dental practice. J Can Dent Assoc. 2006; 72(1):75-80. View

2.
Thali M, Markwalder T, Jackowski C, Sonnenschein M, Dirnhofer R . Dental CT imaging as a screening tool for dental profiling: advantages and limitations. J Forensic Sci. 2006; 51(1):113-9. DOI: 10.1111/j.1556-4029.2005.00019.x. View

3.
Chuang G, Kuo C . Wavelet descriptor of planar curves: theory and applications. IEEE Trans Image Process. 1996; 5(1):56-70. DOI: 10.1109/83.481671. View

4.
Kirchhoff S, Fischer F, Lindemaier G, Herzog P, Kirchhoff C, Becker C . Is post-mortem CT of the dentition adequate for correct forensic identification?: comparison of dental computed tomograpy and visual dental record. Int J Legal Med. 2008; 122(6):471-9. DOI: 10.1007/s00414-008-0274-y. View

5.
Murray D, Whyte A . Dental panoramic tomography: what the general radiologist needs to know. Clin Radiol. 2002; 57(1):1-7. DOI: 10.1053/crad.2001.0826. View