Mumford–Shah regularization in electrical impedance tomography with complete electrode model. (1st June 2022)

• Record Type: Journal Article
• Authors: Jauhiainen, Jyrki; Seppänen, Aku; Valkonen, Tuomo
• Is Part Of: Inverse problems. Volume 38:Number 6(2022)
• Publication Date: 2022-06-01
• Subjects: ill-posed inverse problem -- Mumford–Shah functional -- electrical impedance tomography -- image segmentation -- variational regularisation; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/1361-6420/ac5f3a
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: In electrical impedance tomography (EIT), we aim to solve the conductivity within a target body through electrical measurements made on the surface of the target. This inverse conductivity problem is severely ill-posed, especially in real applications with only partial boundary data available. Thus regularization has to be introduced. Conventionally regularization promoting smooth features is used, however, the Mumford–Shah (M–S) regularizer familiar for image segmentation is more appropriate for targets consisting of several distinct objects or materials. It is, however, numerically challenging. We show theoretically through Γ-convergence that a modification of the Ambrosio–Tortorelli approximation of the M–S regularizer is applicable to EIT, in particular the complete electrode model of boundary measurements. With numerical and experimental studies, we confirm that this functional works in practice and produces higher quality results than typical regularizations employed in EIT when the conductivity of the target consists of distinct smoothly-varying regions.