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Optimizing Deep Learning Algorithms for Segmentation of Acute Infarcts on Non–Contrast Material–enhanced CT Scans of the Brain Using Simulated Lesions
PURPOSE: To test the efficacy of lesion segmentation using a deep learning algorithm on non–contrast material–enhanced CT (NCCT) images with synthetic lesions resembling acute infarcts. MATERIALS AND METHODS: In this retrospective study, 40 diffusion-weighted imaging (DWI) lesions in patients with a...
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| Pubblicato in: | Radiol Artif Intell |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Radiological Society of North America
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8328101/ https://ncbi.nlm.nih.gov/pubmed/34350404 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2021200127 |
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