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Regularizations for an all-at-once formulation of the electrical impedance tomography problem

  • Josué D. Díaz-Avalos ORCID logo EMAIL logo and Nelson Mugayar Kuhl ORCID logo
Published/Copyright: November 10, 2025

Abstract

An all-at-once formulation of the inverse problem of electrical impedance tomography (EIT) is proposed, and three regularizations for it are analyzed. Under a set of assumptions made in the context of Banach spaces, an abstract problem is proposed aiming at generalizing the all-at-once formulation of the EIT inverse problem. This abstract problem allows to incorporate several strategies of input data, namely voltage measurements, current measurements, magnitudes of the current density field, and interior power densities. Three regularizations, based on the classic Tikhonov, Ivanov, and Morozov approaches, are proposed for this problem. The existence, stability, and convergence of regularized solutions are proved. Well-known EIT models fit into this abstraction (for instance, the complete electrode model). It turns out that the all-at-once approach provides an alternative formulation of the EIT inverse problem. Numerical tests are performed using the complete electrode model and the previously mentioned strategies.

A EIT models

Here, some examples of EIT models that verify assumptions (A1) and (A2) are provided.

In what follows H 1 / 2 ( Ω ) denotes the space of traces on Ω , H - 1 / 2 ( Ω ) denotes the dual of H 1 / 2 ( Ω ) , , denotes the pairing between H - 1 / 2 ( Ω ) and H 1 / 2 ( Ω ) , and σ ¯ L ( Ω ) is such that ess inf 𝐱 Ω σ ¯ ( 𝐱 ) > 0 . We abbreviate voltage measurement, current measurement, magnitude of current density field, and interior power density as Vol, Cur, Mag, and Pow, respectively.

Continuum model.

The equations of the continuum model for the electric potential u are

(A.1) ( σ ¯ u ) = 0 in  Ω

with Neumann boundary condition

(A.2) σ ¯ u ν = f on  Ω

if a current f is applied, or with Dirichlet boundary condition

(A.3) u = g on  Ω

if a voltage g is applied. Consider the closed subspaces ( 0 s 1 )

H 1 / 2 ( Ω ) { g H 1 / 2 ( Ω ) : Ω g d 𝐬 = 0 } ,
H - 1 / 2 ( Ω ) { f H - 1 / 2 ( Ω ) : f , 1 = 0 } ,
H 1 + s ( Ω ) { u H 1 + s ( Ω ) : Ω u d 𝐬 = 0 } ,
H 0 1 + s ( Ω ) { u H 1 + s ( Ω ) : γ u = 0 } .

Formulation with applied current. Suppose that the current f H - 1 / 2 ( Ω ) is applied at the boundary Ω . Then the electric potential u ¯ H 1 ( Ω ) is obtained ( u ¯ is solution of (A.1) and (A.2)). The resulting voltage on Ω is given by γ u ¯ H 1 / 2 ( Ω ) . In this case, the all-at-once formulation of the EIT inverse problem can be cast into the form of ($\boldsymbol{I}$) with the spaces X , Z = H 1 ( Ω ) , X ~ = H 1 + s ( Ω ) , the map A : L ( Ω ) × X Z defined by

A ( σ , u ) ( w ) = Ω σ u w d 𝐱 - f , γ w ,

and the following choices for each type of observable data (recall that C : L ( Ω ) × X Y ):

  1. Y = H 1 / 2 ( Ω ) , C ( σ , u ) = γ u , and y ¯ = γ u ¯ H 1 / 2 ( Ω ) ,

  2. Y = L 2 ( Ω ) , C ( σ , u ) = σ | u | , and y ¯ = σ ¯ | u ¯ | L 2 ( Ω ) ,

  3. Y = L 1 ( Ω ) , C ( σ , u ) = σ | u | 2 , y ¯ = σ ¯ | u ¯ | 2 L 1 ( Ω ) .

Formulation with applied voltage. Suppose that the voltage g H 1 / 2 ( Ω ) is applied at the boundary Ω . Then, the electric potential u ¯ H 1 ( Ω ) is obtained ( u ¯ is solution of (A.1) and (A.3)). The resulting current on Ω is given by σ ¯ u ¯ ν H - 1 / 2 ( Ω ) . Let w g H 1 ( Ω ) with the property γ w g = g in H 1 / 2 ( Ω ) . In this case, the all-at-once formulation of the EIT inverse problem can be cast into the form of ($\boldsymbol{I}$) with the spaces X , Z = H 0 1 ( Ω ) , X ~ = H 0 1 + s ( Ω ) , the map A : L ( Ω ) × X Z defined by

A ( σ , u ) ( w ) = Ω σ u w d 𝐱 + Ω σ w g w d 𝐱 ,

and the following choices for each type of observable data (recall that C : L ( Ω ) × X Y ):

  1. Y = ( H 1 ( Ω ) ) * , C ( σ , u ) ( w ) Ω σ ( u + w g ) w d 𝐱 , and y ¯ = σ ¯ u ¯ ν γ { ϕ Y : ϕ ( 1 ) = 0 } ,

  2. Y = L 2 ( Ω ) , C ( σ , u ) = σ | ( u + w g ) | , and y ¯ = σ ¯ | u ¯ | L 2 ( Ω ) ,

  3. Y = L 1 ( Ω ) , C ( σ , u ) = σ | ( u + w g ) | 2 , and y ¯ = σ ¯ | u ¯ | 2 L 1 ( Ω ) .

Alternative formulation. From the previous formulations, we have either the voltage-current pair ( γ u ¯ , f ) H 1 / 2 ( Ω ) × H - 1 / 2 ( Ω ) (with u ¯ being solution of (A.1) and (A.2)) or ( g , σ ¯ u ¯ ν ) H 1 / 2 ( Ω ) × H - 1 / 2 ( Ω ) (with u ¯ being solution of (A.1) and (A.3)). An alternative all-at-once formulation of the EIT inverse problem with the weak form of (A.1) as model equation is given in the form of ($\boldsymbol{I}$) with the spaces X = H 1 ( Ω ) , Z = H 0 1 ( Ω ) , Y = H 1 / 2 ( Ω ) × ( H 1 ( Ω ) ) , X ~ = H 1 + s ( Ω ) , and the maps

A : L ( Ω ) × X Z , A ( σ , u ) ( w ) = Ω σ u w d 𝐱 ,
C : L ( Ω ) × X Y , C ( σ , u ) = ( γ u , { w Ω σ u w d 𝐱 } ) .

Here there are two possibilities for the exact observation y ¯ :

  1. y ¯ = ( γ u ¯ , f γ ) H 1 / 2 ( Ω ) × { ϕ ( H 1 ( Ω ) ) * : ϕ ( 1 ) = 0 } ( u ¯ is solution to (A.1) and (A.2)),

  2. y ¯ = ( g , σ ¯ u ¯ ν γ ) H 1 / 2 ( Ω ) × { ϕ ( H 1 ( Ω ) ) * : ϕ ( 1 ) = 0 } ( u ¯ is solution to (A.1) and (A.3));

(i) for measured voltage-applied current and (ii) for applied voltage-measured current.

Shunt model.

The equations of the shunt model for the electric potential ( u , U ) are

(A.4) ( σ ¯ u ) = 0 in  Ω ,
(A.5) σ ¯ u ν = 0 on  Ω m = 1 M Γ m ,
(A.6) u = U m on  Γ m , m = 1 , , M ,

with

(A.7) Γ m σ ¯ u ν d 𝐬 = 𝒞 m , m = 1 , , M ,

if a current pattern 𝒞 = ( 𝒞 1 , , 𝒞 M ) is applied, or with

(A.8) U m = 𝒱 m , m = 1 , , M ,

if a voltage pattern 𝒱 = ( 𝒱 1 , , 𝒱 M ) is applied. Consider the closed subspaces ( 0 s 1 )

1 + s = { ( u , U ) H 1 + s ( Ω ) × M : ( γ m u ) m = 1 M = U } ,
1 + s = { ( u , U ) H 1 + s ( Ω ) × M : ( γ m u ) m = 1 M = U } ,
0 1 + s = { u H 1 + s ( Ω ) : ( γ m u ) m = 1 M = 0 } .

Formulation with applied current. Suppose that the current pattern 𝒞 M is applied through electrodes Γ 1 , , Γ M . Then, the electric potential ( u ¯ , U ¯ ) 1 is obtained ( ( u ¯ , U ¯ ) is solution of (A.4)–(A.6), and (A.7)). The resulting voltage on the electrodes is given by U ¯ M . In this case, the all-at-once formulation of the EIT inverse problem can be cast into the form of ($\boldsymbol{I}$) with the spaces X , Z = 1 , X ~ = 1 + s , the map A : L ( Ω ) × X Z defined by

A ( σ , ( u , U ) ) ( w , W ) = Ω σ u w d 𝐱 - m = 1 M 𝒞 m W m ,

and the following choices for each type of observable data (recall that C : L ( Ω ) × X Y ):

  1. Y = M , C ( σ , ( u , U ) ) = U , and y ¯ = U ¯ M ,

  2. Y = L 2 ( Ω ) , C ( σ , ( u , U ) ) = σ | u | , and y ¯ = σ ¯ | u ¯ | L 2 ( Ω ) ,

  3. Y = L 1 ( Ω ) , C ( σ , ( u , U ) ) = σ | u | 2 , and y ¯ = σ ¯ | u ¯ | 2 L 1 ( Ω ) .

Formulation with applied voltage. Suppose that the voltage pattern V M is applied through electrodes Γ 1 , , Γ M . Then, the electric potential u ¯ H 1 ( Ω ) is obtained ( ( u ¯ , V ) is solution of (A.4)–(A.6), and (A.8)). The resulting current on the electrodes is given by ( σ ¯ u ¯ ν , γ e m ) m = 1 M M , where e 1 , , e M are functions in H 1 ( Ω ) with the property γ m e m = 1 and γ m e m = 0 for m m . Let w 𝒱 H 1 ( Ω ) with the property ( γ m w 𝒱 ) m = 1 M = 𝒱 . In this case, the all-at-once formulation of the EIT inverse problem can be cast into the form of ($\boldsymbol{I}$) with the spaces X , Z = 0 1 , X ~ = 0 1 + s , the map A : L ( Ω ) × X Z defined by

A ( σ , u ) ( w ) = Ω σ u w d 𝐱 + Ω σ w 𝒱 w d 𝐱 ,

and the following choices for each type of observable data (recall that C : L ( Ω ) × X Y ):

  1. Y = M , C ( σ , u ) = ( Ω σ ( u + w 𝒱 ) e m d 𝐱 ) m = 1 M , and y ¯ = ( σ ¯ u ¯ ν , γ e m ) m = 1 M M ,

  2. Y = L 2 ( Ω ) , C ( σ , u ) = σ | ( u + w 𝒱 ) | , and y ¯ = σ ¯ | u ¯ | L 2 ( Ω ) ,

  3. Y = L 1 ( Ω ) , C ( σ , u ) = | ( u + w 𝒱 ) | 2 , and y ¯ = σ ¯ | u ¯ | 2 L 1 ( Ω ) .

Alternative formulation. From the previous formulations, we have either the voltage-current pair ( U ¯ , 𝒞 ) M × M (with ( u ¯ , U ¯ ) being solution of (A.4)–(A.6), and (A.7)) or ( 𝒱 , ( σ ¯ u ¯ ν , γ e m ) m = 1 M ) M × M (with u ¯ being solution of (A.4)–(A.6), and (A.8)). An alternative all-at-once formulation of the EIT inverse problem with the weak form of (A.4)–(A.6) as model equation is given in the form of ($\boldsymbol{I}$) with the spaces X = 1 , Z = 0 1 , Y = M × M , X ~ = 1 + s , and the maps

A : L ( Ω ) × X Z , A ( σ , ( u , U ) ) ( w ) = Ω σ u w d 𝐱 ,
C : L ( Ω ) × X Y , C ( σ , ( u , U ) ) = ( U , ( Ω σ u e m d 𝐱 ) m = 1 M ) .

Here there are two possibilities for the exact observation y ¯ :

  1. y ¯ = ( U ¯ , 𝒞 ) M × M ( ( u ¯ , U ¯ ) is solution of (A.4)–(A.6), and (A.7)),

  2. y ¯ = ( 𝒱 , ( σ ¯ u ¯ ν , γ e m ) m = 1 M ) M × M ( u ¯ is solution of (A.4)–(A.6), and (A.8));

(i) for measured voltage-applied current and (ii) for applied voltage-measured current.

Gap model.

The equations of the gap model for the electric potential ( u , U ) are

( σ ¯ u ) = 0 in  Ω ,
σ ¯ u ν = 0 on  Ω m = 1 M Γ m ,
σ ¯ u ν = const on  Γ m , m = 1 , , M ,
1 | Γ m | Γ m u d 𝐬 = U m on  Γ m , m = 1 , , M ,

with σ ¯ u ν | Γ m = 𝒞 m | Γ m | for m = 1 , , M if a current pattern 𝒞 = ( 𝒞 1 , , 𝒞 M ) is applied, or with U m = 𝒱 m for m = 1 , , M if a voltage pattern 𝒱 = ( 𝒱 1 , , 𝒱 M ) is applied. The same instances presented for the shunt model work here, but with the subspaces

1 + s = { ( u , U ) H 1 + s ( Ω ) × M : ( 1 | Γ m | Γ m γ m u d 𝐬 ) m = 1 M = U } ,
1 + s = { ( u , U ) H 1 + s ( Ω ) × M : ( 1 | Γ m | Γ m γ m u d 𝐬 ) m = 1 M = U } ,
0 1 + s = { u H 1 + s ( Ω ) : ( 1 | Γ m | Γ m γ m u d 𝐬 ) m = 1 M = 0 } ,

the functions e 1 , , e M with the property Γ m γ m e m d 𝐬 = | Γ m | and γ m e m = 0 for m m , and a function w 𝒱 with the property ( 1 | Γ m | Γ m γ m w 𝒱 d 𝐬 ) m = 1 M = 𝒱 .

Smoothened complete electrode model.

In [19] was proposed the smoothened complete electrode model, which replaces the contact impedances of the complete electrode model with contact admittance functions capable to vanish on some subsets of the electrodes. It can be said that the contact admittances are represented by functions ζ 1 , , ζ M satisfying ζ m L ( m ) , ζ m 0 a.e. on m , and ζ m 0 . Therefore, it suffices to replace the contact impedances z 1 , , z M by ζ 1 , , ζ M in the instances that were proposed for the complete electrode model.

B First order approximations

Bellow the first order approximations of the model maps considered in Section 6.

Model map with applied current.

In this case, x = ( u , U ) and X = Z = H 1 ( Ω ) × M . The first order approximation A k : L ( Ω ) × X Z of A at ( σ k , ( u k , U k ) ) is given by

A k ( σ , ( u , U ) ) = Q ( u , U ) + S σ + φ ,

with Q : X Z , S : L ( Ω ) Z , φ Z defined by

( Q ( u , U ) ) ( w , W ) Ω σ k u w d 𝐱 + m = 1 M 1 z m Γ m ( γ m u - U m ) ( γ m w - W m ) d 𝐬 ,
( S σ ) ( w , W ) Ω σ u k w d 𝐱 , and φ ( w , W ) - Ω σ k u k w d 𝐱 - m = 1 M 𝒞 m W m .

Model map with applied voltage.

In this case, x = u and X = Z = H 1 ( Ω ) . The first order approximation A k : L ( Ω ) × X Z of A at ( σ k , u k ) is given by

A k ( σ , u ) = Q u + S σ + φ ,

with Q : X Z , S : L ( Ω ) Z , φ Z defined by

( Q u ) ( w ) Ω σ k u w d 𝐱 + m = 1 M 1 z m Γ m γ m u γ m w d 𝐬 ,
( S σ ) ( w ) Ω σ u k w d 𝐱 , and φ ( w ) - Ω σ k u k w d 𝐱 - m = 1 M 1 z m Γ m 𝒱 m γ m w d 𝐬 .

Alternative model map.

In this case, x = ( u , U ) , X = H 1 ( Ω ) × M , and Z = H 1 ( Ω ) . The first order approximation A k : L ( Ω ) × X Z of A at ( σ k , ( u k , U k ) ) is given by

A k ( σ , ( u , U ) ) = Q ( u , U ) + S σ + φ ,

with Q : X Z , S : L ( Ω ) Z , φ Z defined by

( Q ( u , U ) ) ( w ) Ω σ k u w d 𝐱 + m = 1 M 1 z m Γ m ( γ m u - U m ) γ m w d 𝐬 ,
( S σ ) ( w ) Ω σ u k w d 𝐱 , and φ ( w ) - Ω σ k u k w d 𝐱 .

For magnitudes of current density field and interior power density data the first order approximations are function of ( σ , u ) in all cases: σ | u | is approximated with ( σ , u ) σ | u k | + σ k | u k | - 1 u k u - σ k | u k | , and σ | u | 2 is approximated with ( σ , u ) σ | u k | 2 + 2 σ k u k u - 2 σ k | u k | 2 .

References

[1] U. G. Abdulla, V. Bukshtynov and S. Seif, Cancer detection through electrical impedance tomography and optimal control theory: Theoretical and computational analysis, Math. Biosci. Eng. 18 (2021), no. 4, 4834–4859. 10.3934/mbe.2021246Search in Google Scholar PubMed

[2] B. J. Adesokan, B. Jensen, B. Jin and K. Knudsen, Acousto-electric tomography with total variation regularization, Inverse Problems 35 (2019), no. 3, Article ID 035008. 10.1088/1361-6420/aaece5Search in Google Scholar

[3] A. Adler and D. Holder, Electrical Impedance Tomography: Methods, History and Applications, CRC Press, Boca Raton, 2021. 10.1201/9780429399886Search in Google Scholar

[4] H. Ammari, E. Bonnetier, Y. Capdeboscq, M. Tanter and M. Fink, Electrical impedance tomography by elastic deformation, SIAM J. Appl. Math. 68 (2008), no. 6, 1557–1573. 10.1137/070686408Search in Google Scholar

[5] A.-P. Calderón, On an inverse boundary value problem, Seminar on Numerical Analysis and its Applications to Continuum Physics, Brazilian Mathematical Society, Rio de Janeiro (1980), 65–73. Search in Google Scholar

[6] P. Caro and K. M. Rogers, Global uniqueness for the Calderón problem with Lipschitz conductivities, Forum Math. Pi 4 (2016), Paper No. E2. 10.1017/fmp.2015.9Search in Google Scholar

[7] E. Casas, K. Kunisch and C. Pola, Regularization by functions of bounded variation and applications to image enhancement, Appl. Math. Optim. 40 (1999), no. 2, 229–257. 10.1007/s002459900124Search in Google Scholar

[8] A. Charalambopoulos, V. Markaki and D. Kourounis, The inverse conductivity problem via the calculus of functions of bounded variation, Math. Methods Appl. Sci. 43 (2020), no. 8, 5032–5072. 10.1002/mma.6251Search in Google Scholar

[9] M. Cheney, D. Isaacson and J. C. Newell, Electrical impedance tomography, SIAM Rev. 41 (1999), no. 1, 85–101. 10.1137/S0036144598333613Search in Google Scholar

[10] K. Cheng, D. Isaacson, J. Newell and D. Gisser, Electrode models for electric current computed tomography, IEEE Trans. Biomed. Eng. 36 (1989), no. 9, 918–924. 10.1109/10.35300Search in Google Scholar PubMed PubMed Central

[11] J. Dardé and S. Staboulis, Electrode modelling: The effect of contact impedance, ESAIM Math. Model. Numer. Anal. 50 (2016), no. 2, 415–431. 10.1051/m2an/2015049Search in Google Scholar

[12] M. Gehre, B. Jin and X. Lu, An analysis of finite element approximation in electrical impedance tomography, Inverse Problems 30 (2014), no. 4, Article ID 045013. 10.1088/0266-5611/30/4/045013Search in Google Scholar

[13] M. Hanke, B. Harrach and N. Hyvönen, Justification of point electrode models in electrical impedance tomography, Math. Models Methods Appl. Sci. 21 (2011), no. 6, 1395–1413. 10.1142/S0218202511005362Search in Google Scholar

[14] B. Harrach, Uniqueness and Lipschitz stability in electrical impedance tomography with finitely many electrodes, Inverse Problems 35 (2019), no. 2, Article ID 024005. 10.1088/1361-6420/aaf6fcSearch in Google Scholar

[15] G. Holler, K. Kunisch and R. C. Barnard, A bilevel approach for parameter learning in inverse problems, Inverse Problems 34 (2018), no. 11, Article ID 115012. 10.1088/1361-6420/aade77Search in Google Scholar

[16] S. Hubmer, K. Knudsen, C. Li and E. Sherina, Limited-angle acousto-electrical tomography, Inverse Probl. Sci. Eng. 27 (2019), no. 9, 1298–1317. 10.1080/17415977.2018.1512983Search in Google Scholar

[17] P. Hungerländer, B. Kaltenbacher and F. Rendl, Regularization of inverse problems via box constrained minimization, Inverse Probl. Imaging 14 (2020), no. 3, 437–461. 10.3934/ipi.2020021Search in Google Scholar

[18] K. V. Huynh and B. Kaltenbacher, Some application examples of minimization based formulations of inverse problems and their regularization, Inverse Probl. Imaging 15 (2021), no. 3, 415–443. 10.3934/ipi.2020074Search in Google Scholar

[19] N. Hyvönen and L. Mustonen, Smoothened complete electrode model, SIAM J. Appl. Math. 77 (2017), no. 6, 2250–2271. 10.1137/17M1124292Search in Google Scholar

[20] V. K. Ivanov, On linear problems which are not well-posed, Dokl. Akad. Nauk SSSR 145 (1962), 270–272. Search in Google Scholar

[21] B. Jensen, A. Kirkeby and K. Knudsen, Feasibility of acousto-electric tomography, Inverse Problems 40 (2024), no. 7, Article ID 075007. 10.1088/1361-6420/ad4669Search in Google Scholar

[22] B. Jin and P. Maass, An analysis of electrical impedance tomography with applications to Tikhonov regularization, ESAIM Control Optim. Calc. Var. 18 (2012), no. 4, 1027–1048. 10.1051/cocv/2011193Search in Google Scholar

[23] B. Kaltenbacher, Regularization based on all-at-once formulations for inverse problems, SIAM J. Numer. Anal. 54 (2016), no. 4, 2594–2618. 10.1137/16M1060984Search in Google Scholar

[24] B. Kaltenbacher, Minimization based formulations of inverse problems and their regularization, SIAM J. Optim. 28 (2018), no. 1, 620–645. 10.1137/17M1124036Search in Google Scholar

[25] B. Kaltenbacher and K. Van Huynh, Iterative regularization for constrained minimization formulations of nonlinear inverse problems, Comput. Optim. Appl. 81 (2022), no. 2, 569–611. 10.1007/s10589-021-00343-xSearch in Google Scholar PubMed PubMed Central

[26] S. Kim, O. Kwon, J. K. Seo and J.-R. Yoon, On a nonlinear partial differential equation arising in magnetic resonance electrical impedance tomography, SIAM J. Math. Anal. 34 (2002), no. 3, 511–526. 10.1137/S0036141001391354Search in Google Scholar

[27] Y. Li, N. Wang, L. Fan, P. Zhao, J. Li, L. Huang and Z. Wang, Robust electrical impedance tomography for biological application: A mini review, Heliyon 9 (2023), no. 4, Article ID e15195. 10.1016/j.heliyon.2023.e15195Search in Google Scholar PubMed PubMed Central

[28] T. d. C. Martins, A. K. Sato, F. S. d. Moura, S. de Camargo , E. D. L. B. O. L. Silva, T. B. R. Santos, Z. Zhao, K. Moeller, M. B. P. Amato, J. L. Mueller, R. G. Lima and M. de Sales Guerra Tsuzuki, A review of electrical impedance tomography in lung applications: Theory and algorithms for absolute images, Annu. Rev. Control 48 (2019), 442–471. 10.1016/j.arcontrol.2019.05.002Search in Google Scholar PubMed PubMed Central

[29] V. A. Morozov, Choice of parameter in solving functional equations by the method of regularization, Dokl. Akad. Nauk SSSR 175 (1967), 1225–1228. Search in Google Scholar

[30] A. Nachman and B. Street, Reconstruction in the Calderón problem with partial data, Comm. Partial Differential Equations 35 (2010), no. 2, 375–390. 10.1080/03605300903296322Search in Google Scholar

[31] A. Nachman, A. Tamasan and J. Veras, A weighted minimum gradient problem with complete electrode model boundary conditions for conductivity imaging, SIAM J. Appl. Math. 76 (2016), no. 4, 1321–1343. 10.1137/15M100897XSearch in Google Scholar

[32] J. Nieminen, K. Zevenhoven, P. Vesanen, Y. Hsu and R. Ilmoniemi, Current-density imaging using ultra-low-field mri with adiabatic pulses, Magnetic Resonance Imaging 32 (2014), no. 1, 54–59. 10.1016/j.mri.2013.07.012Search in Google Scholar PubMed

[33] E. Somersalo, M. Cheney and D. Isaacson, Existence and uniqueness for electrode models for electric current computed tomography, SIAM J. Appl. Math. 52 (1992), no. 4, 1023–1040. 10.1137/0152060Search in Google Scholar

[34] A. Tamasan and A. Timonov, A regularized weighted least gradient problem for conductivity imaging, Inverse Problems 35 (2019), no. 4, Article ID 045006. 10.1088/1361-6420/aaf2fdSearch in Google Scholar

[35] A. Tikhonov, Solution of incorrectly formulated problems and the regularization method, Sov. Math. Dokl. 4 (1963), 1035–1038. Search in Google Scholar

[36] C. R. Vogel and M. E. Oman, Iterative methods for total variation denoising, SIAM J. Sci. Comput. 14 (1996), 227–238. 10.1137/0917016Search in Google Scholar

[37] T. Widlak and O. Scherzer, Hybrid tomography for conductivity imaging, Inverse Problems 28 (2012), no. 8, Article ID 084008. 10.1088/0266-5611/28/8/084008Search in Google Scholar

Received: 2025-04-30
Revised: 2025-10-03
Accepted: 2025-10-19
Published Online: 2025-11-10

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