Table 5.

Summary of tracking methods (segmentation metrics are given in Table 2). CT: computed tomography, CTA: computed tomography angiography, MR: magnetic resonance.

Author	Testing Dataset	Synthetic Data Used	Metrics Results
Guo et al. [12]	8 CT volumes (3D-IRCADb-01)	No	$Ac=0.97,Sens=0.66,Spec=0.98$
	(http://www.ircad.fr/research/3dircadb/)
	(accessed on 5 May 2019)
Lebre et al. [13]	20 CT (3D-IRCADb-01) volumes	Yes	$Ac=0.97,Sens=0.69,Spec=0.98,$
	(http://www.ircad.fr/research/3dircadb/)		$PPV=0.61,FPR=0.01,FNR=0.32$
	(accessed on 5 May 2019)
	and 40 MR volumes from internal dataset		$Ac=0.98,Sens=0.54,Spec=0.98$
			$PPV=0.3,FPR=0.01,FNR=0.45$
Zeng et al. [14]	6 CTA volumes	Yes	$Ac=0.98,Sens=0.8,Spec=0.99$
Sangsefidi et al. [15]	50 CT volumes, including	Yes	$Ac=0.93,Sens=0.93,Spec=0.93,$
	20 CT (3D-IRCADb-01) volumes		$DSC=0.93,JSC=0.88$
	(http://www.ircad.fr/research/3dircadb/)
	(accessed on 5 May 2019)
Yang et al. [16]	10 CT datasets (SLIVER07 [51])	No	$FP$
Zeng et al. [17]	6 CTA volumes	Yes	$Ac=0.98,Sens=0.8,Spec=0.99$
Yan et al. [18]	6 CTA volumes	No	$Ac=0.97,Sens=0.79,Spec=0.98,$
			$ϵ=1.5\%$
Chi et al. [19]	10 CT scans	No	$Ac=0.98,RR=99\%$
Bauer et al. [20]	15 contrast enhanced CT	Yes	$FN=0.26\%$
Alhonnoro et al. [21]	CT	No	$RMSE$
Esneault et al. [22]	CT	No	$Visual$
Kaftan et al. [23]	30 CT scans	No	$Visual$