{'fraction_non_alphanumeric': 0.019320453031312457, 'fraction_numerical': 0.008660892738174551, 'mean_word_length': 5.337552742616034, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A novel image processing technique for 3D volumetric analysis of severely resorbed alveolar sockets with CBCT.

BACKGROUND
The aim of this study was to present and validate a novel procedure for the quantitative volumetric assessment of extraction sockets that combines cone-beam computed tomography (CBCT) and image processing techniques.


METHODS
The CBCT dataset of 9 severely resorbed extraction sockets was analyzed by means of two image processing software, Image J and Mimics, using manual and automated segmentation techniques. They were also applied on 5-mm spherical aluminum markers of known volume and on a polyvinyl chloride model of one alveolar socket scanned with Micro-CT to test the accuracy.


RESULTS
Statistical differences in alveolar socket volume were found between the different methods of volumetric analysis (P<0.0001). The automated segmentation using Mimics was the most reliable and accurate method with a relative error of 1.5%, considerably smaller than the error of 7% and of 10% introduced by the manual method using Mimics and by the automated method using ImageJ.


CONCLUSIONS
The currently proposed automated segmentation protocol for the three-dimensional rendering of alveolar sockets showed more accurate results, excellent inter-observer similarity and increased user friendliness. The clinical application of this method enables a three-dimensional evaluation of extraction socket healing after the reconstructive procedures and during the follow-up visits.