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Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models

Research article (IEEE Journal of Biomedical and Health Informatics, 2015) · cited 50× · AI/ML
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Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models

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Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models is a scholarly article[1].

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  • Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models's instance of is recorded as scholarly article[2].

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Jacek M. Zurada

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/infant-brain-extraction-in-t1-weighted-mr-images-using-bet-and-refinement-using-lcdg-and-mgrf-models
MLA “Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/infant-brain-extraction-in-t1-weighted-mr-images-using-bet-and-refinement-using-lcdg-and-mgrf-models.
BibTeX @misc{4ortxyz_infant-brain-extraction-in-t1-weighted-mr-images-using-bet-and-refinement-using-lcdg-and-mgrf-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models}}, year = {2026}, url = {https://4ort.xyz/entity/infant-brain-extraction-in-t1-weighted-mr-images-using-bet-and-refinement-using-lcdg-and-mgrf-models}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models — https://4ort.xyz/entity/infant-brain-extraction-in-t1-weighted-mr-images-using-bet-and-refinement-using-lcdg-and-mgrf-models (retrieved 2026-05-24)

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