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Table 8 The algorithms with good results on B-mode phantom 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

RPCA

LSADM\(\bullet\)

1.455

3.582

MC

RPCA-GD\(\bullet\)

6.118

3.165

RPCA

L1F

2.595

1.038

MC

ScGrassMC

4.123

1.338

RPCA

DECOLOR

7.015

2.847

LRR

EALM\(\bullet\)

10.899

3.681

RPCA

RegL1-ALM

4.352

3.700

LRR

IALM\(\bullet\)

2.469

3.681

RPCA

GA\(\circ\)

0.032

3.680

LRR

ADM**

0.668

0.024

RPCA

GM\(\circ\)

0.153

3.713

LRR

LADMAP

0.363

3.681

RPCA

MoG-RPCA

4.691

3.359

LRR

FastLADMAP

0.802

3.681

RPCA

noncvxRPCA\(\bullet\)

0.110

3.681

LRR

ROSL

0.421

3.712

RPCA

NSA1\(\bullet\)

1.407

3.602

TTD

3WD\(\bullet\)

1.942

2.964

RPCA

NSA2\(\bullet\)

1.537

3.568

TTD

MAMR

2.784

3.154

RPCA

flip-SPCP-sum-SPG

276

3.695

TTD

RMAMR

6.776

2.289

RPCA

flip-SPCP-max-QN

138

3.695

TTD

ADMM\(\circ\)*

3.627

0.794

RPCA

Lag-SPCP-SPG*

5.010

1.598

NMF

NMF-MU

2.143

3.681

RPCA

Lag-SPCP-QN*

7.219

0.685

NMF

NMF-PG

8.774

3.565

RPCA

FW-T*

0.715

3.073

NMF

NMF-ALS

2.406

3.681

RPCA

BRPCA-MD\(\bullet\)

283

3.724

NMF

NMF-ALS-OBS

2.710

3.681

RPCA

BRPCA-MD-NSS\(\bullet\)

291

3.511

NMF

PNMF

16.815

3.681

RPCA

VBRPCA

4.627

3.692

NMF

ManhNMF

2.292

3.662

RPCA

PRMF

1.522

3.522

NMF

NeNMF

0.066

3.681

RPCA

TFOCS-EC\(\bullet\)

9.131

3.349

NMF

LNMF**

0.204

0.279

RPCA

GoDec

0.095

3.681

NMF

ENMF

13.546

3.681

RPCA

SSGoDec

1.459

3.679

NMF

nmfLS2

0.320

3.681

RPCA

GreGoDec

0.229

3.681

NMF

Semi-NMF

0.154

2.604

ST

GRASTA

1.321

1.156

NMF

Deep-Semi-NMF

0.156

3.681

MC

FPC

49.672

2.454

NMF

iNMF

1.482

3.650

MC

GROUSE**

1.580

0.068

NMF

DRMF\(\bullet\)*

2.461

3.497

MC

IALM-MC

6.992

3.690

TD

HoSVD

0.532

3.681

MC

LMaFit

0.314

3.300

TD

HoRPCA-S-NCX

89.622

3.693

MC

LRGeomCG

0.757

3.723

TD

Tucker-ADAL

258

3.573

MC

MC-NMF\(\circ\)

0.585

3.423

TD

Tucker-ALS

0.130

3.681

MC

OR1MP\(\circ\)

0.096

3.365

    
  1. The algorithms with \(\circ\) are the 3 new algorithms work on processed data, which are defective on original data. The algorithms with \(\bullet\) are sensitive to structured peak pixels and work after logarithmic processing. Three algorithms with ** get good results on original envelope data but are defective on processed data. The algorithms with * give pure backgrounds