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Automatic cephalometric landmark detection using Zernike moments and template matching

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Abstract

Cephalometry is an essential clinical and research tool in orthodontics. It has been used for decades to obtain absolute and relative measures of the craniofacial skeleton. Since manual identification of predefined anatomical landmarks is a very tedious approach, there is a strong need for automated methods. This paper explores the use of Zernike moment-based global features for initial landmark estimation and computing small expectation window for each landmark. Using this expectation window and local template matching based on ring and central projection method, a closer approximation of landmark position is obtained. A smaller search window based on this approximation is used to find the exact location of landmark positions based on template matching using a combination of sum of squared distance and normalized cross-correlation. The system was tested on 18 commonly used landmarks using a dataset of 85 randomly selected cephalograms. A total of 89.5 % of the localization of 18 selected landmarks are within a window of \(\le \!\!\pm 2\text{ mm}\). The average mean error for the 18 landmarks is 1.84 mm and average SD of mean error is 1.24.

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  1. Department of Computer Science, Punjabi University, Patiala, Punjab, India

    Amandeep Kaur & Chandan Singh

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  1. Amandeep Kaur
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  2. Chandan Singh
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Correspondence to Amandeep Kaur.

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Kaur, A., Singh, C. Automatic cephalometric landmark detection using Zernike moments and template matching. SIViP 9, 117–132 (2015). https://doi.org/10.1007/s11760-013-0432-7

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