Stomatology ›› 2026, Vol. 46 ›› Issue (9): 658-662.doi: 10.13591/j.cnki.kqyx.2026.09.003

• Basic and Clinical Research • Previous Articles     Next Articles

Analysis of jaw bone CBCT based on motion blur modeling and inverse filtering enhancement

ZHANG Hengguo(), PAN Yufei, WANG Guoqiang, SUN Xiaoxi   

  1. College & Hospital of Stomatology, Anhui Medical University, Anhui Provincial Key Laboratory of Oral Diseases Research, Hefei 230032, China
  • Received:2026-04-20 Online:2026-09-28 Published:2026-09-20

Abstract:

Objective To evaluate the feasibility of inverse filtering for cone-beam computed tomography(CBCT) assessment in dental implantology and to establish a workflow integrating inverse filtering enhancement with CTAn-based bone microstructural analysis, so as to improve the accuracy of peri-implant bone tissue assessment. Methods CBCT data from 48 patients who underwent implant treatment between January 1, 2022 and December 31, 2024 were retrospectively analyzed. After preprocessing, images were restored using point spread function-based motion blur modeling and frequency-domain Wiener inverse filtering, followed by three-dimensional visualization. Pre- and post-processed images were imported into CTAn for three-dimensional microstructural analysis of peri-implant bone. Bone volume fraction(BV/TV), trabecular number(Tb.N), and structure model index(SMI) were measured. Results Compared with the original images, the processed CBCT images showed clearer peri-implant bone boundaries, trabecular architecture, and local high-density structures. CTAn analysis demonstrated significantly increased BV/TV and Tb.N, and significantly decreased SMI after processing(P<0.05). Conclusion Inverse filtering is feasible for postoperative CBCT assessment in dental implantology. It enables CBCT evaluation to extend from morphological observation to quantitative bone microstructural analysis, improving the assessment of peri-implant bone status and providing support for postoperative follow-up and individualized treatment.

Key words: dental implant, cone-beam computed tomography, inverse filtering, bone microstructural analysis

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