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Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT
The volume of pelvic hematoma at CT has been shown to be the strongest independent predictor of major arterial injury requiring angioembolization in trauma victims with pelvic fractures, and also correlates with transfusion requirement and mortality. Measurement of pelvic hematomas (unopacified extr...
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| Pubblicato in: | J Digit Imaging |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer International Publishing
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7064706/ https://ncbi.nlm.nih.gov/pubmed/31172331 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10278-019-00207-1 |
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