| Title |
Cephalometric image analysis and measurement for orthognathic surgery
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, May 2001
|
| DOI | 10.1007/bf02345280 |
| Pubmed ID | |
| Authors |
J. Yang, X. Ling, Y. Lu, M. Wei, G. Ding |
| Abstract |
Automatic identification of landmarks in cephalometry is very important and useful for orthognathic surgery. A computerised automatic cephalometric analysis system (CACAS), based on image processing, is presented. For an original X-ray image, median filtering and histogram equalisation are used to improve image quality. The edge of an X-ray image is detected by a wavelet transform and Canny filter. Seventeen landmarks in cephalometry are successfully identified by knowledge-based edge tracing and changeable templates. Seventy-three measurements based on distances, angles and ratios between landmarks are computed automatically. The reliability of the landmarks and the validity of the measurements are compared for automatic and manual operation. The values of measurements obtained by CACAS are more precise and reliable: the mean error for linear measurements is less than 0.9mm; the mean error for angular measurements is less than 1.2 degrees. The rate of validity is over 80%, even if the image quality is poor. For an image with a high signal-to-noise ratio, the rate of validity of landmarking and measurements using the CACAS system is over 90%. |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 18% |
| Other | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Postgraduate | 3 | 14% |
| Lecturer | 2 | 9% |
| Other | 5 | 23% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 36% |
| Engineering | 5 | 23% |
| Nursing and Health Professions | 1 | 5% |
| Agricultural and Biological Sciences | 1 | 5% |
| Psychology | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 May 2017.
All research outputs
#8,535,684
of 25,374,917 outputs
Outputs from Medical & Biological Engineering & Computing
#547
of 2,053 outputs
Outputs of similar age
#14,306
of 42,349 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#3
of 4 outputs
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