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A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics

Evolutionary Biology(2020)10.1007/s11692-020-09508-8Source: DataRank Database

A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics is a research paper published in Evolutionary Biology (2020). On theSindex it has a DataRank of 1.7. It has been cited 60 times, with 47 citing works in its 1-hop citation network.

N/A

1.7DataRank · unranked

Scored on demand from live citation data

Open Access60 citations · 47 citing works in its network

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Linked data & code

doi

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (5 grants)Impact (FWCI 11.40)OA: greenTopics (19)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 37%Citation Network 63%

Base Score Contribution

0.617

From this paper's citation signal

Citation Network Contribution

1.1

From 37 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 47 citers.

ALPACA: A fast and accurate computer vision approach for automated landmarking of three‐dimensional biological structures
Methods in Ecology and Evolution2021126 citations45 referencesContributes 0.108
A Critical Comparison Between Template-Based and Architecture-Reused Deep Learning Methods for Generic 3D Landmarking of Anatomical Structures
Lecture notes in computer science20249 citations28 referencesContributes 0.082
Automated landmarking via multiple templates
PLoS ONE202216 citations37 referencesContributes 0.077
Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability
Scientific Reports202410 citations34 referencesContributes 0.071
Carapace Morphological Characteristics of Chinese Mitten Crab (Eriocheir sinensis) from Emerging Origins Revealed via Geometric Morphometrics
Animals20255 citations34 referencesContributes 0.053

Authors (9)

J. David Aponte ORCID,David C. Katz ORCID,Wei Liu ORCID,Lucas Lo Vercio ORCID,Nils D. Forkert ORCID

Live enrichment

PubMed:33583965 PMC:PMC7880197 OpenAlex:https://openalex.org/W3041903417

National Institutes of Health

Grant: R01 01DE019638

Canadian Institutes of Health Research

Grant: Foundation grant

Natural Sciences and Engineering Research Council of Canada

Grant: 238992-17

Canadian Foundation for Innovation

Grant: 36262

NIDCR NIH HHS

Grant: R01 DE019638

FWCI

11.40

Citation Percentile

1.0%

Influential Citations

Citation Trend

2020

2021

2022

2023

2024

2025

2026

greenLicense: https://www.springer.com/tdm

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/7880197

GREENhttps://www.biorxiv.org/content/biorxiv/early/2019/12/12/2019.12.11.873182.full.pdf

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/7880197

publisherhttps://link.springer.com/content/pdf/10.1007/s11692-020-09508-8.pdf

publisherhttps://link.springer.com/article/10.1007/s11692-020-09508-8/fulltext.html

Fields of Study

Morphological variations and asymmetryCell Image Analysis TechniquesAI in cancer detectionBiologyMedicineComputer Science

Keywords

LandmarkMorphometricsArtificial intelligenceImage registrationComputer sciencePattern recognition (psychology)Computer visionImage (mathematics)BiologyGeometryMicro-computed TomographyAnatomical LandmarkDeep Learning

Sustainable Development Goals

SDG 0: Sustainable cities and communities