Simulation inverse problems of reconstruction of image data using patterned electrical impedance tomography female breast

Abstract

This article analyzes the performance of the Electrical Impedance Tomography (EIT) technique in the diagnosis of breast cancer. The simulations used EIDORS (Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software) and OCTAVE, a computational tool for numerical calculation. We compared three algorithms: prior Laplace, NOSER and Tikhonov. The NOSER algorithm obtained the best classification according to performance metrics of proximity between neoplasms, where this factor changes the resolution of the reconstruction images generated depending on the chosen algorithm.

Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

“…A comparison between three algorithms: prior Laplace, Newton's One-Step Error Reconstructor (NOSER), and Tikhonov have been made. Among the three-reconstruction algorithm, The NOSER algorithm achieved the best results due to the good classification performance metrics of proximity between neoplasms, as this factor alter the resolution of the reconstruction images generated based on the algorithm used [85]. Gowry et al in [86] have directed their study into finding out whether high-speed EIT would be able to identify and distinguish the changes in conductivity with recurring Blood-volume changes and also to be able to determine the capability of the usage of these indications to extricate the benign regions from the malignant regions inside the breast.…”