Evidence map›Paper›PMID 41139750›Full record

ArticleClinical oral investigations2025

Feasibility and accuracy assessment of AI-driven incisor restoration using 3D point cloud data.

Xiaohan Ma, Guofen Lin, Shengnan Zhao, Xuechao Zou, Huixin Xie, Min Tang

Abstract read
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In one paragraph

Article in Clinical oral investigations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiaohan MaDepartment of Prosthodontics, Beijing Stomatological Hospital, Capital Medical University, No. 9 Fanjiacun, Fengtai District, Beijing, 100070, Beijing, China. maxiaohan923@163.com.
Guofen Lin *Stomatology Hospital, School of Stomatology, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Zhejiang University School of Medicine Affiliated Stomatological Hospital, No. 166, Qiutao North Road, Shangcheng District, Hangzhou, 310000, Zhejiang Province, China.
Shengnan Zhao *Department of Stomatology, Peking University People's Hospital, No. 11 Xizhimen South Street, Beijing, 100044, Xicheng District, China.
Xuechao ZouSchool of Computer Science and Technology, Beijing Jiaotong University, No. 3 Shangyuancun, Beijing, 100044, Haidian District, China.
Huixin XieDepartment of Prosthodontic Technology Center, Beijing Stomatological Hospital, Capital Medical University, No. 9 Fanjiacun, Beijing, 100070, Fengtai District, China.
Min TangGuangxi Clinical Research Center for Craniofacial Deformity, Department of Orthodontics, Guangxi Medical University College of Stomatology, Nanning, 530021, Guangxi, China. tangmin622@163.com.

Funding

Capital Medical University Affiliated Beijing Stomatological Hospital Clinical Research Incubation Project 25-09-25Guangxi Natural Science Foundation General Program 2025GXNS- FAA069412National Clinical Key Specialty Construction Project CZ000037The Research and Development Project of Stomatology Hospital Zhejiang University School of Medicine RD2023JCEL06
6 · The paper itself

Abstract

objectivesThis study introduces an open-source intelligent anterior tooth restoration method utilizing a point cloud completion network and evaluates its accuracy compared to traditional manual design. MATERIALS AND

methodsA total of 209 digital dental models from patients treated at Beijing Stomatological Hospital (Jan 2024-Jan 2025) were analyzed. Missing maxillary right central incisors were simulated using Geomagic Wrap. The study was divided into two groups: manual design (MD) and AI-generated (AI-G). The AI-G group utilized an AdaPoinTr-based model. Reconstruction accuracy was quantified via L1/L2 Chamfer Distance (CD), F-Score, and Hausdorff Distance (HD). STATISTICS: Paired t-test, Wilcoxon signed-rank tests (α=0.05).

resultsThe MD group exhibited superior local accuracy [L1-CD, MD (9.9171 ± 1.4654) vs. AI-G (15.2144 ± 0.2917), P<0.001] and global matching [L2-CD, MD (2.9709 ± 1.3945) vs. AI-G (6.7731 ± 0.3179, P<0.001) compared to AI-G. Microstructural retention (F-Score) also favored MD [MD 58.4955 (IQR: 11.8238) vs. AI-G 34.6080 (IQR: 0.6612), P<0.001]. However, extreme error control (HD) showed no significant difference [MD 0.0490 mm (IQR: 0.1094 mm) vs. AI-G 0.1264 mm (IQR: 0.0073 mm), P=0.058]. AI-G demonstrated more stable error distribution (IQR: 0.0073 mm vs. 0.1094 mm).

conclusionsThis study introduces an innovative AdaPoinTr network for reconstructing the missing central incisor. Though slightly less accurate than manual design, the AI approach exhibits better stability and consistency, promising for intelligent prosthodontics. CLINICAL RELEVANCE: This study validates the feasibility of AI-driven point cloud completion networks in 3D reconstruction tasks for missing central incisors, providing new research directions for the intelligent development of digital prosthodontics.

Indexed as

Cloud ComputingComputer-Aided DesignDental Prosthesis DesignDental Restoration, PermanentImaging, Three-DimensionalIncisorFeasibility StudiesHumansModels, DentalAIDental prosthesis designIncisorPoint cloud completion

Identifiers

PMID41139750

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.