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Table 3 Difference in net flow between manual segmentation in relation to machine learning and conventional (commercially available) automated segmentation

From: Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification

  Net Flow Absolute Difference (|manual – method|) Correlation
Manual 81.5 ± 24.2 mL   
Machine Learning 80.5 ± 23.7 mLa 1.85 ± 1.80 mLb y = 1.01x + 0.16 r2 = 0.99, p < 0.001
Conventional 80.1 ± 23.2 mLa 3.33 ± 3.18 mLb y = 1.02x – 0.31 r2 = 0.96, p < 0.001
  1. aBoth p < 0.01 (segmentation method vs. manual)
  2. bp < 0.01 (machine learning vs. conventional segmentation in terms of MAD)