Comparing 3d, 2.5d, and 2d approaches to brain image auto-segmentation

HIGHLIGHTS

  • who: Arman Avesta and collaborators from the Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA Department of Biomedical Engineering, Yale University, New Haven, CT, USA have published the paper: Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation, in the Journal: Bioengineering 2023, 10, x FOR PEER REVIEW of /2023/
  • what: This study showed that 3D models are more accurate maintain better performance with limited training data and are faster to train and deploy. The authors comprehensively compared 3D, 2.5D, and 2D approaches to brain . . .

     

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