Evidence map›Paper›PMID 37765897›Full record

ArticleSensors (Basel, Switzerland)2023

Automatic Multiview Alignment of RGB-D Range Maps of Upper Limb Anatomy.

Luca Di Angelo, Paolo Di Stefano, Emanuele Guardiani, Paolo Neri, Alessandro Paoli, Armando Viviano Razionale

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Luca Di AngeloDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-5341-0500
Paolo Di StefanoDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0001-5003-2084
Emanuele GuardianiDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-1623-1474
Paolo NeriDepartment of Civil and Industrial Engineering, University of Pisa, 56122 Pisa, Italy.ORCID 0000-0003-0730-0893
Alessandro PaoliDepartment of Civil and Industrial Engineering, University of Pisa, 56122 Pisa, Italy.ORCID 0000-0002-1918-3033
Armando Viviano RazionaleDepartment of Civil and Industrial Engineering, University of Pisa, 56122 Pisa, Italy.ORCID 0000-0001-7110-3857
University of L'Aquila · ITUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital representations of anatomical parts are crucial for various biomedical applications. This paper presents an automatic alignment procedure for creating accurate 3D models of upper limb anatomy using a low-cost handheld 3D scanner. The goal is to overcome the challenges associated with forearm 3D scanning, such as needing multiple views, stability requirements, and optical undercuts. While bulky and expensive multi-camera systems have been used in previous research, this study explores the feasibility of using multiple consumer RGB-D sensors for scanning human anatomies. The proposed scanner comprises three Intel

Indexed as

ForearmUpper ExtremityAlgorithmsHandHumansNeural Networks, Computer3D optical scanningautomatic point cloud alignmentdepth camerasneural networkupper limb anatomy

Identifiers

PMID37765897
PMCPMC10534679
OpenAlexW4387115194

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.