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Table 4 Segmentation accuracy with root-mean-squared-error (RMSE) and volume difference ( δ V ) on pre and post data for both submitted algorithms (IC to UTB) and fixed-models

From: Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge

  Pre data Post data
  RMSE (mm) |δV| (ml) RMSE (mm) |δV| (ml)
IC 0.72 (0.5) 2.87 (2.0) 9.52 (8.2) 4.79 (2.9)
MV 1.42 (0.7) 38.08 (6.7) 9.20 (8.8) 4.15 (5.7)
SY 0.17 (0.1) 12.87 (2.8) 9.22 (9.3) 10.19 (3.9)
HB n.a. n.a. n.a. 20.16 (10.3)
YL 1.03 (0.4) 0.62 (0.7) 6.34 (8.2) 2.77 (2.3)
KCL 1.33 (0.6) 2.24 (2.2) 9.20 (8.3) 3.10 (2.3)
UTA 0.36 (0.3) 3.24 (2.6) 10.72 (8.0) 3.54 (2.5)
UTB 0.52 (0.5) 3.10 (2.2) 8.91 (8.2) 1.25 (1.5)
2-SD n.a. 7.51 (3.6) n.a. 17.7 (10.1)
3-SD n.a. 12.73 (8.3) n.a. 7.64 (3.7)
4-SD 0.15 (0.1) 12.74 (8.3) 11.69 (7.5) 11.98 (8.5)
6-SD n.a. n.a. n.a. 15.47 (8.5)
FWHM n.a. 70.52 (38.4) 7.67 (8.2) 6.61 (5.9)
  1. The standard deviation of each metric is quoted in brackets. Symbols (†) for pre and () for post denote algorithms that could only be tested on a subset of the complete set of images. Abbreviations: n.a. data not available or could not be computed.