Evidence map›Paper›PMID 36826962›Full record

ArticleJournal of imaging2023

Guidelines for Accurate Multi-Temporal Model Registration of 3D Scanned Objects.

Kate J Benfield, Dylan E Burruel, Trevor J Lujan

Abstract read
In one paragraph

Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Anisotropic wear behavior of meniscus: Influence of cross-shear and loading magnitude.Journal of the mechanical behavior of biomedical materials · 2026
    Article
  2. Article
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.

Kate J BenfieldBiomedical Engineering Doctoral Program, Boise State University, Boise, ID 83725, USA.
Dylan E BurruelDepartment of Mechanical and Biomedical Engineering, Boise State University, Boise, ID 83725, USA.
Trevor J LujanDepartment of Mechanical and Biomedical Engineering, Boise State University, Boise, ID 83725, USA.

Funding

VPS35 D620N inhibits autophagy through disrupted hyaluronic acid-CD44 signalingP20GM109095 · NIGMS · BOISE STATE UNIVERSITY · PI OXFORD, JULIA THOM · 2014 to 2023
$22.7M
NIGMS NIH HHS P20 GM109095NIGMS NIH HHS P20GM109095
6 · The paper itself

Abstract

Changes in object morphology can be quantified using 3D optical scanning to generate 3D models of an object at different time points. This process requires registration techniques that align target and reference 3D models using mapping functions based on common object features that are unaltered over time. The goal of this study was to determine guidelines when selecting these localized features to ensure robust and accurate 3D model registration. For this study, an object of interest (tibia bone replica) was 3D scanned at multiple time points, and the acquired 3D models were aligned using a simple cubic registration block attached to the object. The size of the registration block and the number of planar block surfaces selected to calculate the mapping functions used for 3D model registration were varied. Registration error was then calculated as the average linear surface variation between the target and reference tibial plateau surfaces. We obtained very low target registration errors when selecting block features with an area equivalent to at least 4% of the scanning field of view. Additionally, we found that at least two orthogonal surfaces should be selected to minimize registration error. Therefore, when registering 3D models to measure multi-temporal morphological change (e.g., mechanical wear), we recommend selecting multiplanar features that account for at least 4% of the scanning field of view. For the first time, this study has provided guidelines for selecting localized object features that can provide accurate 3D model registration for 3D scanned objects.

Indexed as

feature matchingfiducial markerhuman tibiaimage registrationiterative closest pointkneemechanical wearregistration errorstructured light 3D scanning

Identifiers

PMID36826962
PMCPMC9966291

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.