Edge Extraction Algorithm using Linear Prediction Model on Dental X-ray Images
TL;DR: The LP residual of the input image is found to provide better edges as compared to the conventional methods and the edge map obtained by the LP method is compared with previous work on zero frequency resonator (ZFR) based edge extraction and is finding to give a better edge map.
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Abstract: paper focuses edge extraction from dental x-ray images for the root canal procedure, using the linear prediction (LP) The major issues of processing the dental X-ray images are caused due to the misalignment and the variation in the contrast, by the very modality of acquisition Also the differences in the shapes and orientations of the teeth pose yet another difficulty in the processing Thus, in order to overcome these challenges, the LP residual based approach is used in this paper to obtain better root canal edge information In the present work, the input image is processed by the 10 th order LP method to obtain LP residual image The LP residual of the input image is found to provide better edges as compared to the conventional methods Also the edge map obtained by the LP method is compared with previous work (7) on zero frequency resonator (ZFR) based edge extraction and is found to give a better edge map Effectiveness of the LP residual method is confirmed by the visual inspection of the edge map and also from the subjective evaluation
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Citations
Feature extraction in dental radiographs in human extracted and permanent dentition
Kanika Lakhani,Bhawna Minocha,Neeraj Gugnani +2 more
- 21 Sep 2016
TL;DR: The feature extraction applied over the radiographs, once the edge detection process is accomplished, derives combinations of the defects to get around the problems while still describing the problem areas with sufficient accuracy.
Feature Extraction in Permanent Human Dentition Radiographs
Kanika Lakhani,Bhawna Minocha,Neeraj Gugnani +2 more
- 01 Jan 2017
TL;DR: The feature extraction applied over the radiographs, once the edge detection process is accomplished, derives combinations of the defects to get around the problems while still describing the problem areas with sufficient accuracy.
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