Evidence map›Paper›PMID 42281011›Full record

ArticleSensors (Basel, Switzerland)2026

An Annotation-Free Pipeline for 3D Auricular Bowl Atlas Construction and Statistical Shape Modelling from Surface Scans.

Tongxu Zhang, Tony Kwok Wing Lee, Jiebin Huang, Kam Lun Leung, Siu Ngor Fu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

5 authors.

Tongxu ZhangDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Tony Kwok Wing LeeDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.ORCID 0000-0001-5620-3286
Jiebin HuangDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Kam Lun LeungDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.ORCID 0000-0001-5992-1566
Siu Ngor FuDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.

Funding

The Research Institute for Sports Sciences and Technology of The Hong Kong Polytechnic University P0043887
6 · The paper itself

Abstract

Three-dimensional (3D) ear morphology is critical for the design of in-the-ear hearing aids, earphones, transcutaneous auricular vagus nerve stimulation (taVNS) electrodes, and auricular reconstruction, yet most existing ear shape models still rely on manually placed landmarks. Here, a fully annotation-free pipeline is presented for constructing a 3D ear atlas and statistical shape model (SSM) of the auricular bowl from 50 surface meshes. Individual ears are iteratively registered to a current atlas using rigid the iterative closest point (ICP) algorithm followed by a bidirectional thin-plate spline (BiTPS) deformation, and dense surface correspondences are established by nearest-neighbour mapping. Registration quality is quantified using mean and maximum nearest-neighbour distance, symmetric Chamfer-L2 distance and coverage. Furthermore, SSM-derived bowl height and width are validated against manual 3D mesh measurements in Geomagic Design X. Across five atlas iterations, the BiTPS pipeline substantially reduces registration errors and increases coverage, and principal component analysis (PCA) derived dimensions show excellent agreement with manual measurements (Pearson r≥0.98, ICC ≥0.98). The proposed framework yields a stable, anatomically plausible ear atlas and an interpretable low-dimensional SSM without manual landmarks, providing a computational basis for the geometric optimization of ear-related medical and wearable devices.

Indexed as

EarImaging, Three-DimensionalModels, StatisticalAlgorithmsHumansModels, AnatomicPrincipal Component Analysis3D ear morphology3D scanningpoint cloudstatistical shape modelsurface registrationthin-plate spline

Identifiers

PMID42281011
PMCPMC13259287

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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.