Evidence map›Paper›PMID 41840145›Full record

ArticleNPJ digital medicine2026

Real-time reconstruction of 3D bone models via very-low-dose protocols.

Yiqun Lin, Haoran Sun, Yongqing Li, Rabia Aslam, Lung Fung Tse, Tiange Cheng, Chun Sing Chui, Wing Fung Yau, Victorine R Le Meur, Meruyert Amangeldy and 5 more

Abstract read
In one paragraph

Article in NPJ digital medicine, 2026. 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

15 authors.

Yiqun Lin *Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China.
Haoran Sun *Koln 3D Technology (Medical) Limited, Hong Kong SAR, China.
Yongqing LiDepartment of Physics, Beihang University, Beijing, China.
Rabia AslamKoln 3D Technology (Medical) Limited, Hong Kong SAR, China.
Lung Fung TseUnion Hospital, Hong Kong SAR, China.
Tiange ChengDental Materials Science, Division of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Chun Sing ChuiDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong SAR, China.
Wing Fung YauKoln 3D Technology (Medical) Limited, Hong Kong SAR, China.
Victorine R Le MeurKoln 3D Technology (Medical) Limited, Hong Kong SAR, China.
Meruyert AmangeldyKoln 3D Technology (Medical) Limited, Hong Kong SAR, China.
Kiho ChoDental Materials Science, Division of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Yinyu YeDepartment of Management Science and Engineering, Stanford University, Stanford, CA, USA.
James ZouDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Wei ZhaoDepartment of Physics, Beihang University, Beijing, China. zhaow20@buaa.edu.cn.
Xiaomeng LiDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China. eexmli@ust.hk.

Funding

Hong Kong Innovation and Technology Fund PRP/041/22FXNational Natural Science Foundation of China No. 12175012Natural Science Foundation of Zhejiang Province No. LZ23A050002
6 · The paper itself

Abstract

Patient-specific bone models are essential for designing surgical guides and preoperative planning, as they enable the visualization of intricate anatomical structures. However, traditional CT-based approaches for creating bone models are limited to preoperative use due to the low flexibility and high radiation exposure of CT and time-consuming manual delineation. Here, we introduce Semi-Supervised Reconstruction with Knowledge Distillation (SSR-KD), a fast and accurate AI framework to reconstruct high-quality bone models from biplanar X-rays in 30 seconds, with an average error under 1.0 mm, eliminating the dependence on CT and manual work. Additionally, high tibial osteotomy simulation was performed by experts on reconstructed bone models, demonstrating that bone models reconstructed from biplanar X-rays have comparable clinical applicability to those annotated from CT. Overall, our approach accelerates the process, reduces radiation exposure, enables intraoperative guidance, and significantly improves the practicality of bone models, offering transformative applications in orthopedics.

Identifiers

PMID41840145
PMCPMC13139424

What OpenQuestion holds

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Registered trials

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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.