Table 1.

Summary of reviewed documents.

Authors	Year	Segmentation Category	Method	Autom. Level	Dim.	Database	Results
Bae et al. [19]	1993	Threshold	Grey-level thresholding	Semi	2D	Private	0.985 DSC with mean percent error within 10%.
Gao et al. [20]	1996	Edge	Parametrically deformable contour model	Fully	3D	Private	13.2% of the results required user modifications.
Soler et al. [21]	1997	Edge	Deformable models	Fully	3D	Private	Claimed to be comparable to manual segmentations.
Yoo et al. [22]	2000	Threshold	Threshold	Fully	2D	Private	3.41% error.
Pan and Dawant [23]	2001	Edge	Level sets	Fully	Both	Private	[0.874, 0.963] average similarities.
Saitoh et al. [24]	2002	Threshold	Threshold	Fully	3D	Private	∼20 min computation time.
Masumoto et al. [25]	2003	Region	Differences between time-phase images	Fully	3D	Private	67% volume ratio average; 32% in the worst cases.
Lim et al. [26]	2004	Region	Watershed	Fully	2D	Private	Only qualitative.
Liu et al. [27]	2005	Edge	GVF snake	Semi	2D	Private	5.3% median value of the difference ratios.
Lim et al. [28]	2006	Semantic	Labeling-based search	Fully	2D	Private	96% average correctness; 3% average error rate.
Beichel et al. [29]	2007	Region	Graph cuts	Semi	3D	Private	5.2% average overlap error.
Massoptier and Casciaro [30]	2008	Edge	Active contour	Fully	3D	Private	94.2% mean DSC.
Heimann et al. [31]	2009	Several	Majority Voting	Both	Both	Private	5% overlap error; −0.7 volume difference; 0.8 average distance; 1.7 RMS distance; 19.1 max distance.
Akram et al. [32]	2010	Threshold	Global Threshold	Fully	3D	Private	0.96 average accuracy; 0.0017 std; 96% accurately segmented; 4% poorly segmented.
Oliveira et al. [33]	2011	Edge	Level sets	Semi	2D	SLiver07	82.05 overall score.
Linguraru et al. [34]	2012	Region	Graph cuts	Fully	3D	Private; SLiver07	2.2 VOE.
Li et al. [35]	2013	Edge	Fuzzy clustering and level set	Fully	2D	Private	0.9986 average accuracy; 0.9989 average specificity.
Platero et al. [37]	2014	Region	Graph cuts	Semi	3D	SLiver07	76.3 maximum score; 0.973 DSC.
Mostafa et al. [38]	2015	Cluster	ABC optimization	Fully	2D	Private	93.73% accuracy; 84.82% average SI.
Dou et al. [39]	2016	NN	3D DSN	Fully	3D	SLiver07	5.42% VOE; 0.79 mm ASSD.
Christ et al. [14]	2017	NN	CFCN	Fully	2D	3D-IRCADb01	94.3% mean DSC.
Hiraman [40]	2018	NN	CNN	Fully	2D	SLiver07	12.07% average VOE; −1.96% RVD; 2.25 mm ASSD; 2.60 mm RMSD; 43.01 mm MSSD.
Wang et al. [41]	2019	NN	CNN	Fully	3D	Private	$0.94\pm 0.06$ DSC.
Almotairi et al. [42]	2020	NN	SegNet	Fully	3D	3D-IRCADb01	94.57% overall accuracy.
Ayalew et al. [44]	2021	NN	U-Net	Fully	2D	3D-IRCADb01; LiTS	0.9612 DSC.
Scicluna [46]	2022	NN	UNet; VGG16UNetC	Fully	2D	CHAOS	85.84 mean score; 97.85 DSC; 80.33 RAVD; 94.80 ASSD score; 70.38 MSSD.
Ezzat et al. [48]	2023	NN	CNN	Fully	2D	Private	98.80% accuracy.
Shao et al. [49]	2024	NN	AC-Net	Fully	3D	Private; LiTS	0.90 DSC; 0.82 JC; 0.92 recall; 0.89 precision; 11.96 HD; 4.59 ASSD.

ABC: Artificial Bee Colony; AC-Net: Attention Connect Network; ASSD: average symmetric surface distance; CFCN: cascaded fully CNN; CNN: convolutional neuronal network; DSC: Dice Similarity Coefficient; DSN: deeply supervised network; GVF: gradient vector flow; HD: Hausdorff distance; JC: Jaccard coefficient; MSSD: maximum symmetric surface distance; NN: neuronal network; RAVD: relative absolute volume difference; RMS: root mean square; RMSD: root mean square Symmetric Surface Distance; RVD: relative volume difference; SI: similarity index; std: standard deviation; VOE: volumetric overlap error.