An image classification deep-learning algorithm for shrapnel detection from ultrasound images.
Saved in:
| Title: | An image classification deep-learning algorithm for shrapnel detection from ultrasound images. |
|---|---|
| Authors: | Snider EJ; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA. eric.j.snider3.civ@mail.mil., Hernandez-Torres SI; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA., Boice EN; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA. |
| Source: | Scientific reports [Sci Rep] 2022 May 19; Vol. 12 (1), pp. 8427. Date of Electronic Publication: 2022 May 19. |
| Publication Type: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S. |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 35589931 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: An image classification deep-learning algorithm for shrapnel detection from ultrasound images. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Snider+EJ%22">Snider EJ</searchLink>; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA. eric.j.snider3.civ@mail.mil.<br /><searchLink fieldCode="AU" term="%22Hernandez-Torres+SI%22">Hernandez-Torres SI</searchLink>; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA.<br /><searchLink fieldCode="AU" term="%22Boice+EN%22">Boice EN</searchLink>; Engineering Technology and Automation Combat Casualty Care Research Team, United States Army Institute of Surgical Research, Ft. Sam Houston, TX, USA. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2022 May 19; Vol. 12 (1), pp. 8427. <i>Date of Electronic Publication: </i>2022 May 19. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, U.S. Gov't, Non-P.H.S. – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101563288 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=35589931 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-022-12367-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 8427 Titles: – TitleFull: An image classification deep-learning algorithm for shrapnel detection from ultrasound images. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Snider EJ – PersonEntity: Name: NameFull: Hernandez-Torres SI – PersonEntity: Name: NameFull: Boice EN IsPartOfRelationships: – BibEntity: Dates: – D: 19 M: 05 Text: 2022 May 19 Type: published Y: 2022 Identifiers: – Type: issn-electronic Value: 2045-2322 Numbering: – Type: volume Value: 12 – Type: issue Value: 1 Titles: – TitleFull: Scientific reports Type: main |
| ResultId | 1 |