Evidence map›Paper›PMID 42221878›Full record

ArticleFrontiers in medical technology2026

A registration method for total hip arthroplasty navigation system based on point cloud alignment.

Zhenling Wang, Qiurui He, Xinwei Yue

Abstract read
In one paragraph

Article in Frontiers in medical technology, 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

3 authors.

Zhenling WangThe School of Internet of Things Engineering, Wuxi University of Technology, Wuxi, China.
Qiurui HeThe School of Software, Luoyang Normal University, Luoyang, China.
Xinwei YueThe School of Information and Communication Engineering, Beijing Information Science and Technology University (BISTU), Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hip replacement surgery requires high precision in aligning intraoperative anatomical structure localization with preoperative imaging spatial alignment. To address the registration difficulties caused by the limited number and sparse distribution of intraoperative probe acquisition points, our paper proposes a method based on point cloud registration between an intraoperative probe tracked by a passive binocular optical tracking system (NDI) and a CT surface, aimed at improving patient registration accuracy in intraoperative navigation scenarios. First, we define the patient-registration problem and describe the methods for acquiring pre-operative and intra-operative data. Subsequently, the centroids of the NDI optical tracking markers are employed as common features shared by the patient and image spaces, and an initial registration is performed using a three-point method. Finally, an improved ICP algorithm is used to perform accurate registration between the two point clouds, and the registration results are validated using a fixture platform. In the experiments conducted on 3D-printed acetabular and femoral models, the target registration errors (TRE) of the proposed method for registering the acetabular model and the femoral model are (0.55

Indexed as

ICP algorithmimage point cloud samplingpatient registrationsparse-dense point cloud alignmentsurgical navigation system

Identifiers

PMID42221878
PMCPMC13219043

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.