Evidence map›Paper›PMID 40374780›Full record

ArticleAesthetic plastic surgery2025

Artificial Intelligence Technology in 3D Facial Reconstruction: An Approach to Reutilize 2D Standardized Images in Plastic Surgery.

Yiwen Deng, Ben Wang, Haiyue Jiang

Abstract read
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In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yiwen Deng *Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ben Wang *Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Haiyue JiangPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. jianghaiyue24@126.com.

Funding

CAMS Innovation Fund for Medical Sciences 2021-I2M-1-052National Natural Science Foundation of China 82371796
6 · The paper itself

Abstract

introductionTwo-dimensional (2D) facial photographs serve as crucial data in plastic surgery, and their reuse can yield additional clinical information for reference purposes. The present study presents an approach for three-dimensional (3D) facial reconstruction, wherein the patient's standard facial photograph is imported into a reconstruction algorithm to generate a 3D facial model. This reconstructed model allows for comprehensive observation from various angles, providing accurate representation of the proportion and structural characteristics of the facial contour.

methodsA total of 31 patients were randomly selected, and the frontal and lateral photographs of each patient's face were input into the algorithm for facial 3D reconstruction. The facial subunits were analyzed in terms of their proportions, angles, and lengths. The effectiveness of the reconstruction algorithm was evaluated by comparing the dimensions of each index in both frontal and lateral 2D standardized facial photographs, as well as 3D scans of the patient, along with frontal and lateral perspectives of 3D model generated by the reconstruction algorithm.

resultsThe algorithm-reconstructed 3D model group showed significant correlations with both the standard photograph group and the 3D scan-reconstructed model group in each indicator, thereby indicating the precise reconstruction of patients' facial information through this reconstruction algorithm.

conclusionThe facial 3D reconstruction algorithm possesses the capability to transform 2D photographs into precise 3D digital models, exhibiting efficiency, convenience, speed, and accessibility while accurately capturing the distinctive attributes of facial subunit. This approach facilitates the reutilization of 2D facial photographs, thereby providing a genuine and invaluable tool for clinical practice. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors   www.springer.com/00266 .

Indexed as

Artificial IntelligenceFaceImaging, Three-DimensionalPhotographyPlastic Surgery ProceduresSurgery, PlasticAdultAlgorithmsEstheticsFemaleHumansMaleMiddle AgedYoung Adult3D reconstructionAlgorithmArtificial intelligencePlastic surgery

Identifiers

PMID40374780

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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.