Skip to main content

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.