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Nonlocal atlas-guided multi-channel forest learning for human brain labeling.
Ma G, Gao Y, Wu G, Wu L, Shen D. Ma G, et al. Med Phys. 2016 Feb;43(2):1003-19. doi: 10.1118/1.4940399. Med Phys. 2016. PMID: 26843260 Free PMC article.
PURPOSE: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. ...METHODS: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship …
PURPOSE: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. …
Non-local Atlas-guided Multi-channel Forest Learning for Human Brain Labeling.
Ma G, Gao Y, Wu G, Wu L, Shen D. Ma G, et al. Med Image Comput Comput Assist Interv. 2015 Oct;9351:719-726. doi: 10.1007/978-3-319-24574-4_86. Epub 2015 Nov 18. Med Image Comput Comput Assist Interv. 2015. PMID: 26942235 Free PMC article.
Labeling MR brain images into anatomically meaningful regions is important in many quantitative brain researches. ...In particular, we employ a multi-channel random forest to learn the nonlinear relationship between these hybrid fe …
Labeling MR brain images into anatomically meaningful regions is important in many quantitative brain researches. ...In …