P L Lin1, P Y Huang2, P W Huang3. 1. Department of Computer Science and Information Engineering, Providence University, 200, Taiwan Bld., Shalu, Taichung 43301, Taiwan. Electronic address: lan@pu.edu.tw. 2. Department of Computer Science and Engineering, National Chung Hsing University, Taichung 40227, Taiwan. Electronic address: grances81@gmail.com. 3. Department of Computer Science and Engineering, National Chung Hsing University, Taichung 40227, Taiwan. Electronic address: powhei.huang@msa.hinet.net.
Abstract
BACKGROUND AND OBJECTIVE: Periodontitis involves progressive loss of alveolar bone around the teeth. Hence, automatic alveolar bone loss measurement in periapical radiographs can assist dentists in diagnosing such disease. In this paper, we propose an automatic length-based alveolar bone loss measurement system with emphasis on a cementoenamel junction (CEJ) localization method: CEJ_LG. METHOD: The bone loss measurement system first adopts the methods TSLS and ABLifBm, which we presented previously, to extract teeth contours and bone loss areas from periodontitis radiograph images. It then applies the proposed methods to locate the positions of CEJ, alveolar crest (ALC), and apex of tooth root (APEX), respectively. Finally the system computes the ratio of the distance between the positions of CEJ and ALC to the distance between the positions of CEJ and APEX as the degree of bone loss for that tooth. The method CEJ_LG first obtains the gradient of the tooth image then detects the border between the lower enamel and dentin (EDB) from the gradient image. Finally, the method identifies a point on the tooth contour that is horizontally closest to the EDB. RESULTS: Experimental results on 18 tooth images segmented from 12 periodontitis periapical radiographs, including 8 views of upper-jaw teeth and 10 views of lower-jaw teeth, show that 53% of the localized CEJs are within 3 pixels deviation (∼ 0.15 mm) from the positions marked by dentists and 90% have deviation less than 9 pixels (∼ 0.44 mm). For degree of alveolar bone loss, more than half of the measurements using our system have deviation less than 10% from the ground truth, and all measurements using our system are within 25% deviation from the ground truth. CONCLUSION: Our results suggest that the proposed automatic system can effectively estimate degree of horizontal alveolar bone loss in periodontitis radiograph images. We believe that our proposed system, if implemented in routine clinical practice, can serve as a valuable tool for early and accurate diagnosis of alveolar bone loss in periodontal diseases and also for assessing the status of alveolar bone following various types of non surgical and surgical and regenerative therapy. For overall system improvement, a more objective comparison by using transgingival bone measurement with a periodontal probe as the ground truth and enhancing the localization algorithms of these three critical points are the two major tasks.
BACKGROUND AND OBJECTIVE:Periodontitis involves progressive loss of alveolar bone around the teeth. Hence, automatic alveolar bone loss measurement in periapical radiographs can assist dentists in diagnosing such disease. In this paper, we propose an automatic length-based alveolar bone loss measurement system with emphasis on a cementoenamel junction (CEJ) localization method: CEJ_LG. METHOD: The bone loss measurement system first adopts the methods TSLS and ABLifBm, which we presented previously, to extract teeth contours and bone loss areas from periodontitis radiograph images. It then applies the proposed methods to locate the positions of CEJ, alveolar crest (ALC), and apex of tooth root (APEX), respectively. Finally the system computes the ratio of the distance between the positions of CEJ and ALC to the distance between the positions of CEJ and APEX as the degree of bone loss for that tooth. The method CEJ_LG first obtains the gradient of the tooth image then detects the border between the lower enamel and dentin (EDB) from the gradient image. Finally, the method identifies a point on the tooth contour that is horizontally closest to the EDB. RESULTS: Experimental results on 18 tooth images segmented from 12 periodontitis periapical radiographs, including 8 views of upper-jaw teeth and 10 views of lower-jaw teeth, show that 53% of the localized CEJs are within 3 pixels deviation (∼ 0.15 mm) from the positions marked by dentists and 90% have deviation less than 9 pixels (∼ 0.44 mm). For degree of alveolar bone loss, more than half of the measurements using our system have deviation less than 10% from the ground truth, and all measurements using our system are within 25% deviation from the ground truth. CONCLUSION: Our results suggest that the proposed automatic system can effectively estimate degree of horizontal alveolar bone loss in periodontitis radiograph images. We believe that our proposed system, if implemented in routine clinical practice, can serve as a valuable tool for early and accurate diagnosis of alveolar bone loss in periodontal diseases and also for assessing the status of alveolar bone following various types of non surgical and surgical and regenerative therapy. For overall system improvement, a more objective comparison by using transgingival bone measurement with a periodontal probe as the ground truth and enhancing the localization algorithms of these three critical points are the two major tasks.
Authors: Nektarios Tsoromokos; Sarah Parinussa; Frank Claessen; David Anssari Moin; Bruno G Loos Journal: Int Dent J Date: 2022-05-13 Impact factor: 2.607