Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR) Technique in EIT: A Simulation Study

Tushar Kanti Bera; Samir Kumar Biswas; K. Rajan; J. Nagaraju

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Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR) Technique in EIT: A Simulation Study

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| 15. Juni 2011

Journal of Electrical Bioimpedance

Band 2 (2011): Heft 1 (January 2011)

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Article Category: Articles

Online veröffentlicht: 15. Juni 2011

Seitenbereich: 33 - 47

Eingereicht: 30. März 2011

DOI: https://doi.org/10.5617/jeb.170

Schlüsselwörter
EIT, MoBIIR, Jacobian, Block Matrix-based Multiple Regularization (BMMR), simulated boundary data, conductivity imaging, STR, LMR, normalized projection error, normalized solution error

© 2011 Tushar Kanti Bera, Samir Kumar Biswas, K. Rajan, J. Nagaraju, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Current injection and voltage measurement in EIT for a closed domain (Ω) surrounded by surface electrodes at the domain boundary (∂Ω) (red and blue electrode represent the current and voltage electrodes respectively).

BMMR matrix formation: (a) A matrix formation by defining several block matrices in JTJ matrix, (b) Y matrix formation from A matrix, (c) BMMR matrix or Z matrix formation from Y matrix.

Projection errors (EV) calculated in the conductivity reconstruction at different iterations with different values of λ: (a) with STR, (b) with LMR, (c) with BMMR.

Error in different regularization methods for λ = 0.01: (a) normalized projection errors, (b) normalized solution error norm.

Conductivity reconstruction of the phantom with inhomogeneity (D = 30 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.01): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 30 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 30 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.00011): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 20 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 40 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 35 mm, L = 22.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 35 mm, L = 37.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with inhomogeneity (D = 35 mm, L = 52.5 mm) near electrode No.-3 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with double inhomogeneity (D = 40 mm, L = 37.5 mm) near electrode No.-3 and 15 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with double inhomogeneity (D = 40 mm, L = 52.5 mm) near electrode No.-3 and 15 (λ = 0.01): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with double inhomogeneity (D = 40 mm, L = 50.0 mm) near electrode No.-3 and 7 (λ = 0.0011): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with double inhomogeneity (D = 40 mm, L = 37.5 mm) near electrode No.-3 and 7 (λ = 0.0011): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with tripple inhomogeneity (D = 40 mm, L = 37.5 mm) near electrode No.-1, between electrode No.-6-7 and between electrode No.-11-12 (λ = 0.0001): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR

Conductivity reconstruction of the phantom with tripple inhomogeneity (D = 40 mm, L = 50.0 mm) near electrode No.-1, between electrode No.-6-7 and between electrode No.-11-12 (λ = 0.0011): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR.

Conductivity reconstruction of the phantom with tripple inhomogeneity (D = 40 mm, L = 30.0 mm) near electrode No.-1, between electrode No.-6-7 and between electrode No.-11-12 (λ = 0.00011): (a) original object, (b) image with STR, (c) image with LMR, (d) image with BMMR

CNR, PCR and COC of the conductivity images of Fig.-9

30 mm Dia.	CNR	PCR	COC	IC_Mean
STR	1.94	45.94	2.04	0.25
LMR	1.30	38.46	1.81	0.27
BMMR	2.80	68.02	4.20	0.12

CNR, PCR and COC of the conductivity images of Fig.-6

λ = 0.0001	CNR	PCR	COC	IC_Mean
STR	1.98	46.30	2.05	0.25
LMR	1.12	28.25	1.46	0.34
BMMR	2.67	68.76	4.60	0.11

CNR, PCR and COC of the conductivity images of Fig.-5

λ = 0.01	CNR	PCR	COC	IC_Mean
STR	1.91	37.35	1.52	0.41
LMR	2.07	34.72	1.49	0.40
BMMR	2.67	49.06	2.14	0.24

CNR, PCR and COC of the conductivity images of Fig.-8

20 mm Dia.	CNR	PCR	COC	IC_Mean
STR	0.56	12.73	1.18	0.40
LMR	1.17	20.93	1.32	0.37
BMMR	2.51	50.53	2.46	0.19

CNR, PCR and COC of the conductivity images of Fig.-7

λ = 0.00011	CNR	PCR	COC	IC_Mean
STR	1.94	45.94	2.04	0.25
LMR	1.30	38.46	1.81	0.27
BMMR	2.80	68.02	4.20	0.12

CNR, PCR and COC of the conductivity images of Fig.-12

37.5 mm Dist.	CNR	PCR	COC	IC_Mean
STR	1.79	48.72	2.15	0.24
LMR	1.54	45.90	2.06	0.24
BMMR	2.75	75.33	6.01	0.08

CNR, PCR and COC of the conductivity images of Fig.-13

52.5 mm Dist.	CNR	PCR	COC	IC_Mean
STR	3.44	63.75	3.70	0.13
LMR	3.57	62.77	3.54	0.14
BMMR	3.59	63.77	3.50	0.14

CNR, PCR and COC of the conductivity images of Fig.-10

40 mm Dia.	CNR	PCR	COC	IC_Mean
STR	1.91	53.07	2.29	0.23
LMR	2.14	65.05	3.33	0.16
BMMR	2.98	74.58	5.06	0.10

CNR, PCR and COC of the conductivity images of Fig.-11

22.5 mm Dist.	CNR	PCR	COC	IC_Mean
STR	2.22	48.25	1.72	0.38
LMR	1.86	44.09	1.60	0.41
BMMR	2.61	55.67	2.04	0.30

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Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR) Technique in EIT: A Simulation Study

Article Category: Articles

Online veröffentlicht: 15. Juni 2011

Seitenbereich: 33 - 47

Eingereicht: 30. März 2011

DOI: https://doi.org/10.5617/jeb.170

Schlüsselwörter
EIT, MoBIIR, Jacobian, Block Matrix-based Multiple Regularization (BMMR), simulated boundary data, conductivity imaging, STR, LMR, normalized projection error, normalized solution error

© 2011 Tushar Kanti Bera, Samir Kumar Biswas, K. Rajan, J. Nagaraju, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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CNR, PCR and COC of the conductivity images of Fig.-9

CNR, PCR and COC of the conductivity images of Fig.-6

CNR, PCR and COC of the conductivity images of Fig.-5

CNR, PCR and COC of the conductivity images of Fig.-8

CNR, PCR and COC of the conductivity images of Fig.-7

CNR, PCR and COC of the conductivity images of Fig.-12

CNR, PCR and COC of the conductivity images of Fig.-13

CNR, PCR and COC of the conductivity images of Fig.-10

CNR, PCR and COC of the conductivity images of Fig.-11

Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR) Technique in EIT: A Simulation Study

Article Category: Articles

Online veröffentlicht: 15. Juni 2011

Seitenbereich: 33 - 47

Eingereicht: 30. März 2011

DOI: https://doi.org/10.5617/jeb.170

SchlüsselwörterEIT, MoBIIR, Jacobian, Block Matrix-based Multiple Regularization (BMMR), simulated boundary data, conductivity imaging, STR, LMR, normalized projection error, normalized solution error

© 2011 Tushar Kanti Bera, Samir Kumar Biswas, K. Rajan, J. Nagaraju, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig.1

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CNR, PCR and COC of the conductivity images of Fig.-9

CNR, PCR and COC of the conductivity images of Fig.-6

CNR, PCR and COC of the conductivity images of Fig.-5

CNR, PCR and COC of the conductivity images of Fig.-8

CNR, PCR and COC of the conductivity images of Fig.-7

CNR, PCR and COC of the conductivity images of Fig.-12

CNR, PCR and COC of the conductivity images of Fig.-13

CNR, PCR and COC of the conductivity images of Fig.-10

CNR, PCR and COC of the conductivity images of Fig.-11

Schlüsselwörter
EIT, MoBIIR, Jacobian, Block Matrix-based Multiple Regularization (BMMR), simulated boundary data, conductivity imaging, STR, LMR, normalized projection error, normalized solution error