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Table 5 The algorithms with good results on B-mode simulation data

From: Clutter suppression in ultrasound: performance evaluation and review of low-rank and sparse matrix decomposition methods

Group

Abbreviation

Time

CNR

Group

Abbreviation

Time

CNR

TTD

3WD\(\circ\)

2.027

1.486

RPCA

Lag-SPCP-QN*

2.809

0.494

LRR

ADM

0.563

3.401

RPCA

Lag-SPCP-SPG*

8.961

0.456

RPCA

ALM\(\bullet\)

18.748

1.827

MC

LMaFit

0.424

1.889

RPCA

APG\(\circ\)*

4.229

1.855

MC

LRGeomCG

0.811

1.885

RPCA

APG-PARTIAL\(\circ\)*

3.696

1.860

RPCA

LSADM\(\circ\)

1.454

1.847

RPCA

AS-RPCA

2.180

1.803

TTD

MAMR

1.642

1.781

RPCA

DECOLOR

3.450

1.717

NMF

ManhNMF

1.422

1.903

NMF

Deep-Semi-NMF

0.195

1.903

RPCA

MoG-RPCA

1.710

1.934

NMF

DRMF\(\circ\)*

2.461

1.842

NMF

NeNMF

0.073

1.903

RPCA

DUAL\(\circ\)*

89.410

1.824

NMF

NMF-ALS

1.848

1.903

LRR

EALM\(\bullet\)

0.321

1.903

NMF

NMF-ALS-OBS

1.987

1.903

RPCA

EALM\(\circ\)

4.324

1.840

NMF

nmfLS2

0.206

1.903

NMF

ENMF

9.056

1.903

NMF

NMF-MU

1.643

1.903

LRR

FastLADMAP

0.769

1.903

NMF

NMF-PG

32.465

1.899

RPCA

flip-SPCP-max-QN

102.000

1.835

RPCA

noncvxRPCA

0.100

1.903

RPCA

flip-SPCP-sum-SPG

230.000

1.835

RPCA

NSA1\(\bullet\)

0.255

1.902

MC

FPC

34.877

1.442

TD

OSTD\(\bullet\)*

0.764

1.451

RPCA

FPCP*

0.150

1.875

RPCA

PCP\(\circ\)*

9.978

1.842

RPCA

FW-T\(\circ\)*

0.722

0.370

NMF

PNMF

13.424

1.903

RPCA

GA\(\bullet\)

0.028

1.904

RPCA

PRMF

1.336

1.857

RPCA

GoDec

0.096

1.903

RPCA

R2PCP\(\bullet\)*

1.269

2.024

RPCA

GreGoDec

0.282

1.903

RPCA

RegL1-ALM

3.918

1.833

TD

HoRPCA-S-NCX

112.090

1.836

TTD

RMAMR\(\bullet\)

5.369

1.561

TD

HoSVD

4.493

1.903

LRR

ROSL*

0.369

1.830

LRR

IALM

1.880

1.903

MC

RPCA-GD\(\circ\)

4.946

1.891

RPCA

IALM\(\circ\)*

0.701

1.840

NMF

Semi-NMF

0.134

1.331

RPCA

IALM-BLWS\(\circ\)*

1.800

1.843

RPCA

SSGoDec

1.206

1.903

MC

IALM-MC

5.729

1.848

RPCA

TFOCS-EC\(\bullet\)

6.388

1.903

NMF

iNMF

1.148

1.770

TD

Tucker-ADAL

74.711

1.903

RPCA

L1F\(\bullet\)

1.022

0.817

TD

Tucker-ALS

0.118

1.903

LRR

LADMAP

0.446

1.903

RPCA

VBRPCA

0.306

0.343

  1. The algorithms with \(\circ\) are affected by high peak values and get good results after suppressing peaks. The algorithms with \(\bullet\) only get good results after increasing the dynamic range. The algorithms with * give pure background
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