Ceph-X: development and evaluation of 2D cephalometric system
© The Author(s). 2016
Published: 22 December 2016
Cephalometric analysis and measurements of skull parameters using X-Ray images plays an important role in predicating and monitoring orthodontic treatment. Manual analysis and measurements of cephalometric is considered tedious, time consuming, and subjected to human errors. Several cephalometric systems have been developed to automate the cephalometric procedure; however, no clear insights have been reported about reliability, performance, and usability of those systems. This study utilizes some techniques to evaluate reliability, performance, and usability metric using SUS methods of the developed cephalometric system which has not been reported in previous studies.
In this study a novel system named Ceph-X is developed to computerize the manual tasks of orthodontics during cephalometric measurements. Ceph-X is developed by using image processing techniques with three main models: enhancements X-ray image model, locating landmark model, and computation model. Ceph-X was then evaluated by using X-ray images of 30 subjects (male and female) obtained from University of Malaya hospital. Three orthodontics specialists were involved in the evaluation of accuracy to avoid intra examiner error, and performance for Ceph-X, and 20 orthodontics specialists were involved in the evaluation of the usability, and user satisfaction for Ceph-X by using the SUS approach.
Statistical analysis for the comparison between the manual and automatic cephalometric approaches showed that Ceph-X achieved a great accuracy approximately 96.6%, with an acceptable errors variation approximately less than 0.5 mm, and 1°. Results showed that Ceph-X increased the specialist performance, and minimized the processing time to obtain cephalometric measurements of human skull. Furthermore, SUS analysis approach showed that Ceph-X has an excellent usability user’s feedback.
The Ceph-X has proved its reliability, performance, and usability to be used by orthodontists for the analysis, diagnosis, and treatment of cephalometric.
Cephalometric is a compound latin word includes two distinct terms: cephalo (the head), and metrics (measurements) . Thus, cephalometry is the art of the human head measurements which used to evaluate craniofacial growth. Skull radiographs is involved widely to measure the human head dimensions since several years ago .
Skull relationship can be evaluated by using cephalometric techniques for both horizontally and vertically of five major features through linear and angular measurements. These features are the skeletal maxilla, the skeletal mandible, the cranium and cranial base, the maxillary dentition and the mandibular dentition .
Orthodontics used several techniques for cephalometric analysis and measurements by using angular and linear measurements. Angular analysis is used to establish the relations between the individual sections of the skull, while the linear analysis is used to obtain the distance between two reference points in the skull . Orthodontics usually uses their experiences to locate cephalometric landmarks manually on radiographic images. Unfortunately, the manual process is exposed to human errors such as projection errors during the conversion between the 3-D image and the 2-D image , X-ray film errors due to the clarity and device resolution , and measurements errors due to the human eyes limitation, pencils thickness, and unskilful hands . In addition, the conventional method is also considered tedious and time consuming process taking on average 15 to 20 min from expert specialist to handle each individual case [9, 10].
Computerizing cephalometric have been employed to solve the previous issues, and to offer numerous advantages such as reduce the efforts and times of orthodontic, X-ray enhancement, consistent measurements, pre-surgical simulation, obtain more accurate and reliable results, and more efficient storage, transferring, and archiving data [11, 12]. Since 1986, the Image processing techniques have been applied on cephalometric analysis and landmarks measurements. Several image processing approaches were used to extract the important features of X-Ray images to detect the landmarks for geometrical measurements [13, 14]. Early works were used edge detection technique to locate the landmarks points, and cephalometric classes are then identified by geometrical relations of angles, lines, and intersection and exterior boundaries. Thus, researchers have been focused to develop several systems to automate the analysing and measurements process of cephalometric using several approaches such as resolution pyramid, and Edge enhancement , Pattern matching , Active shape models , Active contours with similarity function , PCNN (pulse coupled neural networks) , Support vector machines , Filtering, Edge tracking, pattern matching, and Active shape models .
Current systems have been developed to transfer the traditional process of cephalometric to be performed automatically using digital devices. Research applied image processing in cephalometric field to transfer X-ray films into computing devices to be stored as images for further processing such as enhancing X-ray images, locating landmark points (either automatically or manually), calculating the angular and linear parameters, and following the case status. In more details, X-ray image enhancements is included in most cephalometric systems by applying specific filters to increase image contrasts such as kalman , S.Ti.F. , unsharp, and Gaussian [24, 25]. Furthermore, cephalometric systems were implemented locating landmark points either manually by allowing specialist to select the interested points in computing screen device, or automatically by allowing system to detect and identify landmarks points using some approaches such as fuzzy logic, and ANN [26, 27]. In addition, some cephalometric systems tried to predict the patient face after surgery , while other research tried to develop and evaluate cephalometric system using three dimension devices [28–30]. There are several studies undertaken to compare the accuracy of digital cephalometric with analogue methods [31, 32]. However, some research reported that the manual approaches are still more convenient to the orthodontics than automatic process even though research have shown that the accuracy of some cephalometric system is higher compared with the traditional methods [7, 33]. Research stated that digital methods can be also lead to some errors such as transferring, magnification, and measurements errors. Particularly, existing systems accuracy were varying between 60 and 80% in automating cephalometric compared with manual process, where the total errors should be not more than 0.59 mm for the x coordinate, and 0.56 mm for the y coordinate to be acceptable . Unfortunately, no research on automatic landmark location archives the previous value . Recent study showed that current cephalometric measurements obtained with the computerized cephalometric systems can be considered reliable, and can be used by the clinician [33, 36, 37]. This findings is supported by study perfomed by Paixão et.al  which compares between manual and automatic process using Dolphin imaging software on 50 subjects (male and female). The study did not show any significance difference between manual and automatic process . Similar findings have been reported by Tikku et al. using 13 linear and 13 angular measurements on 40 subjects, where only 6 among 13 measurements were significant . However, most studies did not emphasize on the usability aspect of the system. In this research, we aim to develop a cephalometric system, and evaluate its accuracy, performance, and usability against manual process. Usablity is considered as an important aspect of user accaptance of a developed system where the System Usability Scale method (SUS) was applied to indicate the user satisisfication and acceptance level of the develop system.
Cephalometric parameters used in this study
Landmark Points (11)
Po - Or
ANS - PNS
Me - Go
S – N
N – A
ANS: Anterior nasal spine
PNS: Posterior nasal spine
Point A: sub spinal
Point B: supramental
Ceph-X was developed by applying some image processing techniques to enhance the X-ray images, locate landmark points, and compute automatically linear and angular cephalometric measurements. Four main models were developed, enhancement model, locating model, computing model, and report generation model.
Locating landmark model
Measurements model was designed mainly to obtain the measurement results for 18 linear and angular parameters (6 angles, 12 lines) through using some geometrical algorithms as described below.
These equations are used mainly to reduce the measurement errors for linear measurements based on the factor scale.
This conversion process is necessary because orthodontics are more familiar to understand angles in degree.
The output of Ceph-X is a data file contains angular and linear results, which generated automatically to be displayed for orthodontics usage as html report.
In this study, two methods have been conducted to evaluate the reliability and usability of Ceph-X, as described in detail below.
Comparison results for linear measurements
Po - Or
ANS - PNS
Me - Go
S – N
N - A
N - B
Comparison results for angular measurements
t - test
Comparison results of performance evaluation
Manual (N = 30)
Automatic (N = 30)
P - Value
SUS approach is used to evaluate the usability of Ceph-X system. SUS approach abbreviation for (System Usability Scale) is used because it proves its reliability, and validity with approximately more than 2800 citations . 20 novice and expert orthodontics were guided to use Ceph-X for analysis and measurements several cephalometric cases. Then, SUS survey was distributed among them, to gather their opinions about Ceph-X. Result of interpreting the SUS scores from participants indicated an excellent usability scale about Ceph-X system.
This study is conducted to provide a clear picture about the possibility of replacing the traditional cephalometric process with the digital one. The study focused mainly to design a usable cephalometric system, and evaluate its reliability and usability for cephalometric analysis and measurements using SUS method. No differences in gender have been found in this study as it is in accordance to findings stated in literature [39, 40]. Ceph-X obtained a high accuracy results with approximately 96.6% compared with traditional method. Data in Tables 2 and 3 showed that there are no significant differences between the Ceph-X and traditional approach in cephalometric measurements. The maximum error results which approximately 1.15, and 0.16 mm for angles and lines respectively, is still acceptable on cephalometric measurements, in agreement with previous studies and acceptable clinically [9, 34, 36, 37]. High accuracy results of Ceph-X was achieved because of system ability to enhance and zoom the X-ray images, and also because we excluded the automatic landmark locating which considered as one of main errors source of digital conversion for cephalometric process as stated previously [33, 35]. The cephalometric measurements (12 linear and 6 angular) used in this study are selected according to the most important landmarks points. These points are easily identified, uniform in outline and reproducible and permits valid quantitative measurements of lines and angles projected from them [39, 40]. The results of this study shows the statistical differences for linear and angular measurements in digital and manual methods are clinically acceptable based on criteria set by [9, 29]. The findings in this study also conforms to the study conducted by  of 50 subjects in terms of cephalometric parameters (6 linear and 8 angular measurements) and mean age. However in this study a single examiner performed manual tracing which can lead to inter examiner error and the reliability of the measurement taken despite of using larger sample of 50 subjects. Inter and intra examiner error is assessment of reliability is important when identifying landmarks measurement in orthodontic studies. In order to avoid intra-examiner error the current study used three orthodontic specialists to obtain the measurements. Mean value of measurement taken by all three of the orthodontics are used in this study to increase the reliability of the study. In addition, result showed that there is no significant difference between the manual and automatic approaches for all the 12 linear and 6 angular parameters used in this study. Study conducted by Tikku et al.  using more parameters (13 linear and 13 angular) measurements of 40 subjects indicated that only 6 out of 13 angular measurement used in the study were statistically significant. Therefore it can be concluded that usage of extra angular measurement as reported in  leads to complicated system which reduces the system usability. Both studies conducted by Tikku et al.  and Paixao et al.  have disregarded the usability aspect of the system which have been addressed in the current study. The SUS method have been used to measure user usability and Ceph-X is developed using measurements which are significant and is it sufficient to be used in routine clinical practice.
The mathematical equations implemented in Ceph-X had enhanced the system accuracy by converting the different measurements unites between the digital and manual process, and by obtaining the linear and angular measurements similar with traditional methods. In addition, Table 4 showed that there is significant differences on time between the comparisons of manual and computerize methods in all of the cephalometric analysis and measurements stages. Thus, Ceph-X proved its efficiency in reducing the orthodontics time, and efforts required for cephalometric process, with performance results approximately more than 10 times if compared with the manual approach. Furthermore, an excellent usability result for the Ceph-X showed that orthodontics are ready to replace the traditional cephalometric process with the computerize methods, where usability score result using the SUS method also showed that users preferred using Ceph-X system instead of the manual approach in disagreement with previous research [7, 34]. Thus, efficiency of Ceph-X system in reducing their time and efforts of cephalometric analysis and measurements, and the additional advantages of computer system were behind the Ceph-X user’s satisfactions. Even though the current study is using 30 subjects intra examiner error was taken into consideration to ensure the reliability and SUS method has been applied to ensure the usability of the study as compared with previous studies [36, 37]. Overall, this study proved the possibility of achieving a high reliability results for cephalometric process if conventional approach was replaced with suitable digital approach, in agreement with the finding of several studies . Ceph-X system had a very small error because it was implemented mathematically to resolve the scaling factors errors and conversion process errors during cephalometric measurement. These results in better speed, accuracy and consistency enhance the overall value of the Ceph-X system for the clinical usage.
This work shows that automatic system for cephalometric analysis and simulation can be achieved if suitable computer system is developed. Ceph-X proved its reliability and usability with clinically acceptable errors to be replaced the manual process for cephalometric measurements. Future studies will be carried out on larger cohort to optimise and eventually increase the land mark point list. Future study will also include study on differences in results obtained based on ethnicity and the possibility to use 3D CT scans.
Ceph-X reduced the time and efforts required for cephalometric process specifically for obtaining cephalometric measurements compared with using the ruler and protractor in manual approach. A cephalometric system supports users with additional digital advantages such as easy storage, archive, access, and transmission patient information, with the ability of image manipulation and processing.
Typical cephalometric system should be included image enhancement, landmarks locating, linear and angular measurements, and report generation models. Automatic landmark locating model should be omitted in cephalometric system because it’s a potential errors source. Ceph-X system is essentially preferred by orthodontics for its reliability, user friendly, and time and effort saving.
Authors would like to thank university of Malaya Hospital for giving the data used in this study, and permission. The authors would like also to acknowledge the University of Malaya Grant (UMRG) RG370-15AFR (Frontier Science).
This article has been published as part of BMC Bioinformatics Volume 17 Supplement 19, 2016. 15th International Conference On Bioinformatics (INCOB 2016): bioinformatics. The full contents of the supplement are available online https://bmcbioinformatics.biomedcentral.com/articles/supplements/volume-17-supplement-19.
Publication of this article was funded by BMC Bioinformatics Committee.
Availability of data and materials
Data will not be shared to keep patient information.
MAAM led the study, developed the Ceph-X system, and structured the whole research. SM and MB assisted in manuscript writing, and performed the statistical analysis. RA led the orthodontic teams to run the experiment, and system evaluation. All authors contributed in this study. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Hence the study is retrospective; we hide the patient information to assure the confidentiality, and privacy of patients.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Stedman T. Stedman’s medical dictionary. Baltimore: William & Wilkins; 1990.Google Scholar
- Steiner CC. Cephalometrics for you and me. Am J Orthod. 1953;39(10):729–55.View ArticleGoogle Scholar
- Proffit WR, Fields Jr HW, Sarver DM. Contemporary orthodontics. United Kingdom: Elsevier Health Sciences; 2014. p. 32-47.Google Scholar
- Delaire J. Maxillary development revisited: relevance to the orthopaedic treatment of Class III malocclusions. Eur J Orthod. 1997;19(3):289–312.View ArticlePubMedGoogle Scholar
- Daskalogiannakis J, van der Linden FP, Miethke RR, McNamara JA. Glossary of orthodontic terms. Chicago: Quintessence Books; 2000.Google Scholar
- Cannon J. An atlas and manual of cephalometric radiography [Book Review]. Aust Orthod J. 1982;7(4):179.Google Scholar
- Celik E, Polat-Ozsoy O, Memikoglu TUT. Comparison of cephalometric measurements with digital versus conventional cephalometric analysis. Eur J Orthod. 2009:cjn105.Google Scholar
- Houston W. The analysis of errors in orthodontic measurements. Am J Orthod. 1983;83(5):382–90.View ArticlePubMedGoogle Scholar
- Chen S-K, Chen Y-J, Yao C-CJ, Chang H-F. Enhanced speed and precision of measurement in a computer-assisted digital cephalometric analysis system. Angle Orthod. 2004;74(4):501–7.PubMedGoogle Scholar
- Chen Y-J, Chen S-K, Chung-Chen Yao J, Chang H-F. The effects of differences in landmark identification on the cephalometric measurements in traditional versus digitized cephalometry. Angle Orthod. 2004;74(2):155–61.PubMedGoogle Scholar
- Xia J, Qi F, Yuan W, Wang D, Qiu W, Sun Y et al., editors. Computer aided simulation system for orthognathic surgery. Computer-Based Medical Systems, 1995. Proceedings of the Eighth IEEE Symposium on; 1995: IEEE.Google Scholar
- Forsyth D, Davis D. Assessment of an automated cephalometric analysis system. Eur J Orthod. 1996;18(1):471–8.View ArticlePubMedGoogle Scholar
- Levy-Mandel A, Venetsanopoulos A, Tsotsos J. Knowledge-based landmarking of cephalograms. Comput Biomed Res. 1986;19(3):282–309.View ArticlePubMedGoogle Scholar
- Parthasarathy S, Nugent S, Gregson P, Fay D. Automatic landmarking of cephalograms. Comput Biomed Res. 1989;22(3):248–69.View ArticlePubMedGoogle Scholar
- Tong W, Nugent S, Jensen G, Fay D, editors. An algorithm for locating landmarks on dental X-rays. Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in; 1989: IEEE.Google Scholar
- Cardillo J, Sid-Ahmed M, editors. An image processing system for the automatic extraction of craniofacial landmarks. Nuclear Science Symposium and Medical Imaging Conference, 1991., Conference Record of the 1991 IEEE; 1991: IEEE.Google Scholar
- Hutton TJ, Cunningham S, Hammond P. An evaluation of active shape models for the automatic identification of cephalometric landmarks. Eur J Orthod. 2000;22(5):499–508.View ArticlePubMedGoogle Scholar
- Romaniuk B, Desvignes M, Revenu M, Deshayes M-J. Shape variability and spatial relationships modeling in statistical pattern recognition. Pattern Recogn Lett. 2004;25(2):239–47.View ArticleGoogle Scholar
- Innes A, Ciesielski V, Mamutil J, John S, editors. Landmark detection for cephalometric radiology images using pulse coupled neural networks. Proc. Int. Conf. on Artificial Intelligence; 2002: Citeseer.Google Scholar
- Chakrabartty S, Yagi M, Shibata T, Cauwenb G, editors. Robust cephalometric landmark identification using support vector machines. Multimedia and Expo, 2003. ICME’03. Proceedings. 2003 International Conference on; 2003: IEEE.Google Scholar
- Yue W, Yin D, Li C, Wang G, Xu T. Automated 2-D cephalometric analysis on X-ray images by a model-based approach. Biomedical Engineering, IEEE Transactions on. 2006;53(8):1615–23.View ArticleGoogle Scholar
- Xinding S, Zhenming X, Changsheng X, Yan W, editors. Adaptive kalman filtering approach of color noise in cephalometric image. Signal Processing, 1996. 3rd International Conference on; 1996: IEEE.Google Scholar
- Frosio I, Borghese NA, editors. Real time enhancement of cephalometric radiographies. Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on; 2006: IEEE.Google Scholar
- Mosleh MA, Baba MS, Himazian N, AL-Makramani B, editors. An image processing system for cephalometric analysis and measurements. Information Technology, 2008. ITSim 2008. International Symposium on; 2008: IEEE.Google Scholar
- Yue W, Yin D, Li C, Wang G, Xu T, editors. Locating large-scale craniofacial feature points on X-ray images for automated cephalometric analysis. Image Processing, 2005. ICIP 2005. IEEE International Conference on; 2005: IEEE.Google Scholar
- Cardillo J, Sid-Ahmed M. An image processing system for locating craniofacial landmarks. Medical Imaging, IEEE Transactions on. 1994;13(2):275–89.View ArticleGoogle Scholar
- El-Feghi I, Sid-Ahmed MA, Ahmadi M. Automatic localization of craniofacial landmarks for assisted cephalometry. Pattern Recogn. 2004;37(3):609–21.View ArticleGoogle Scholar
- Hassan B, van der Stelt P, Sanderink G. Accuracy of three-dimensional measurements obtained from cone beam computed tomography surface-rendered images for cephalometric analysis: influence of patient scanning position. Eur J Orthod. 2009;31(2):129–34.View ArticlePubMedGoogle Scholar
- Swennen GR, Schutyser F. Three-dimensional cephalometry: spiral multi-slice vs cone-beam computed tomography. Am J Orthod Dentofac Orthop. 2006;130(3):410–6.View ArticleGoogle Scholar
- Lagravère MO, Carey J, Toogood RW, Major PW. Three-dimensional accuracy of measurements made with software on cone-beam computed tomography images. Am J Orthod Dentofac Orthop. 2008;134(1):112–6.View ArticleGoogle Scholar
- Ongkosuwito E, Katsaros C, Van’t Hof M, Bodegom J, Kuijpers-Jagtman A. The reproducibility of cephalometric measurements: a comparison of analogue and digital methods. Eur J Orthod. 2002;24(6):655–65.View ArticlePubMedGoogle Scholar
- Sayinsu K, Isik F, Trakyali G, Arun T. An evaluation of the errors in cephalometric measurements on scanned cephalometric images and conventional tracings. Eur J Orthod. 2007;29(1):105–8.View ArticlePubMedGoogle Scholar
- Erkan M, Gurel HG, Nur M, Demirel B. Reliability of four different computerized cephalometric analysis programs. Eur J Orthod. 2011:cjr008.Google Scholar
- Leonardi R, Giordano D, Maiorana F, Spampinato C. Automatic cephalometric analysis: a systematic review. Angle Orthod. 2008;78(1):145–51.View ArticlePubMedGoogle Scholar
- Prabhakar R, Rajakumar P, Karthikeyan M, Saravanan R, Vikram NR, Reddy A. A hard tissue cephalometric comparative study between hand tracing and computerized tracing. J Pharm Bioallied Sci. 2014;6 Suppl 1:S101.View ArticlePubMedPubMed CentralGoogle Scholar
- Paixão MB, Sobral MC, Vogel CJ, Araujo TM. Comparative study between manual and digital cephalometric tracing using Dolphin Imaging software with lateral radiographs. Dent Press J Orthod. 2010;15(6):123–30.View ArticleGoogle Scholar
- Tikku T, Khanna R, Maurya R, Srivastava K, Bhushan R. Comparative evaluation of cephalometric measurements of monitor-displayed images by Nemoceph software and its hard copy by manual tracing. J Oral Biol Craniofacial Res. 2014;4(1):35–41.View ArticleGoogle Scholar
- Brooke J. SUS-A quick and dirty usability scale. Usability Eval Ind. 1996;189(194):4–7.Google Scholar
- Iyyer BS, Bhalajhi SI, Bhalajhi SI. Orthodontics: the art and science. New Delhi: Arya (Medi) Publ.; 2012.Google Scholar
- White S, Pharoah M. Textbook of oral radiology principles and interpretations. New York: Elsevier; 2009.Google Scholar
- Macri V, Wenzel A. Reliability of landmark recording on film and digital lateral cephalograms. Eur J Orthod. 1993;15(2):137–48.View ArticlePubMedGoogle Scholar