Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography
- DOI
- 10.1007/s13239-021-00594-z
- Published
- 2022-01-08
- Container
- Cardiovascular Engineering and Technology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1007/s13239-021-00594-z,
title = {Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography},
author = {Francesca Brutti and Alice Fantazzini and Alice Finotello and Lucas Omar Müller and Ferdinando Auricchio and Bianca Pane and Giovanni Spinella and Michele Conti},
year = {2022},
journal = {Cardiovascular Engineering and Technology},
doi = {10.1007/s13239-021-00594-z},
url = {https://doi.org/10.1007/s13239-021-00594-z}
}RIS
TY - JOUR TI - Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography AU - Francesca Brutti AU - Alice Fantazzini AU - Alice Finotello AU - Lucas Omar Müller AU - Ferdinando Auricchio AU - Bianca Pane AU - Giovanni Spinella AU - Michele Conti PY - 2022 JO - Cardiovascular Engineering and Technology DO - 10.1007/s13239-021-00594-z UR - https://doi.org/10.1007/s13239-021-00594-z ER -
APA
Brutti, F., Fantazzini, A., Finotello, A., Müller, L. O., Auricchio, F., Pane, B., Spinella, G., & Conti, M. (2022). Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography. Cardiovascular Engineering and Technology. https://doi.org/10.1007/s13239-021-00594-z
Source records
- crossref · retrieved 2026-09-26T04:23:14.345Z