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. 2024 Jan 10;26(1):100003. doi: 10.1016/j.jocmr.2023.100003

Table 3.

Segmentation performance derived from different methods. The reported clinical results are represented using the absolute error and relative error between the ground truth and prediction. The best results are shown in bold. SAX2D-M and SAX3D-M represent models that only use the magnitude images as the input. The other methods use both magnitude and velocity images as the input.

Method Dice (%) ASD (mm) EDV (ml) ESV (ml) LVEF (%) KE (mJ)
SAX2D 84.44 ± 6.31 3.31 ± 1.90 19.93(10.39%) 19.43(25.45%) 9.44(18.41%) 0.07(5.61%)
RAW2D 80.02 ± 7.39 4.01 ± 1.87 29.57(17.97%) 32.61(44.54%) 10.92(21.60%) 0.19(13.93%)
SAX3D 82.81 ± 6.69 4.43 ± 4.72 22.80(12.80%) 24.66(32.21%) 10.06(19.07%) 0.14(11.61%)
RAW3D 79.79 ± 7.57 3.68 ± 1.65 24.66(14.32%) 26.82(35.01%) 10.41(21.91%) 0.16(11.61%)
SAX2DF 84.52 ± 6.61 3.14 ± 2.35 20.29(10.55%) 17.38(22.22%) 7.37(13.93%) 0.09(7.04%)
SAX2D-M 81.39 ± 7.42 4.13 ± 2.93 26.26(13.45%) 32.51(45.40%) 21.04(39.37%) 0.15(11.83%)
SAX3D-M 80.71 ± 0.09 5.29 ± 4.80 24.96(13.97%) 38.41(57.66%) 18.88(34.86%) 0.17(13.31%)