1
|
Tian X, Ye J, Zhang T, Zhang L, Liu X, Fu F, Shi X, Xu C. Multi-Path Fusion in SFCF-Net for Enhanced Multi-Frequency Electrical Impedance Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2814-2824. [PMID: 38536679 DOI: 10.1109/tmi.2024.3382338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.
Collapse
|
2
|
Wang Z, Nawaz M, Khan S, Xia P, Irfan M, Wong EC, Chan R, Cao P. Cross modality generative learning framework for anatomical transitive Magnetic Resonance Imaging (MRI) from Electrical Impedance Tomography (EIT) image. Comput Med Imaging Graph 2023; 108:102272. [PMID: 37515968 DOI: 10.1016/j.compmedimag.2023.102272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/04/2023] [Accepted: 07/08/2023] [Indexed: 07/31/2023]
Abstract
This paper presents a cross-modality generative learning framework for transitive magnetic resonance imaging (MRI) from electrical impedance tomography (EIT). The proposed framework is aimed at converting low-resolution EIT images to high-resolution wrist MRI images using a cascaded cycle generative adversarial network (CycleGAN) model. This model comprises three main components: the collection of initial EIT from the medical device, the generation of a high-resolution transitive EIT image from the corresponding MRI image for domain adaptation, and the coalescence of two CycleGAN models for cross-modality generation. The initial EIT image was generated at three different frequencies (70 kHz, 140 kHz, and 200 kHz) using a 16-electrode belt. Wrist T1-weighted images were acquired on a 1.5T MRI. A total of 19 normal volunteers were imaged using both EIT and MRI, which resulted in 713 paired EIT and MRI images. The cascaded CycleGAN, end-to-end CycleGAN, and Pix2Pix models were trained and tested on the same cohort. The proposed method achieved the highest accuracy in bone detection, with 0.97 for the proposed cascaded CycleGAN, 0.68 for end-to-end CycleGAN, and 0.70 for the Pix2Pix model. Visual inspection showed that the proposed method reduced bone-related errors in the MRI-style anatomical reference compared with end-to-end CycleGAN and Pix2Pix. Multifrequency EIT inputs reduced the testing normalized root mean squared error of MRI-style anatomical reference from 67.9% ± 12.7% to 61.4% ± 8.8% compared with that of single-frequency EIT. The mean conductivity values of fat and bone from regularized EIT were 0.0435 ± 0.0379 S/m and 0.0183 ± 0.0154 S/m, respectively, when the anatomical prior was employed. These results demonstrate that the proposed framework is able to generate MRI-style anatomical references from EIT images with a good degree of accuracy.
Collapse
Affiliation(s)
- Zuojun Wang
- The Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong.
| | - Mehmood Nawaz
- The Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong.
| | - Sheheryar Khan
- School of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong
| | - Peng Xia
- The Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong
| | - Muhammad Irfan
- Faculty of Electrical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan
| | | | | | - Peng Cao
- The Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong.
| |
Collapse
|
3
|
Ouypornkochagorn T, Polydorides N, McCann H. Towards continuous EIT monitoring for hemorrhagic stroke patients. Front Physiol 2023; 14:1157371. [PMID: 37089433 PMCID: PMC10115159 DOI: 10.3389/fphys.2023.1157371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
The practical implementation of continuous monitoring of stroke patients by Electrical Impedance Tomography (EIT) is addressed. In a previous paper, we have demonstrated EIT sensitivity to cerebral hemodynamics, using scalp-mounted electrodes, very low-noise measurements, and a novel image reconstruction method. In the present paper, we investigate the potential to adapt that system for clinical application, by using 50% fewer electrodes and by incorporating into the measurement protocol an additional high-frequency measurement to provide an effective reference. Previously published image reconstruction methods for multi-frequency EIT are substantially improved by exploiting the forward calculations enabled by the detailed head model, particularly to make the referencing method more robust and to attempt to remove the effects of modelling error. Images are presented from simulation of a typical hemorrhagic stroke and its growth. These results are encouraging for exploration of the potential clinical benefit of the methodology in long-term monitoring of hemorrhagic stroke.
Collapse
Affiliation(s)
| | - Nick Polydorides
- School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom
| | - Hugh McCann
- School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom
- *Correspondence: Hugh McCann,
| |
Collapse
|
4
|
Touboul A, Zouari F, Minciullo L, Modak D, Lee RMV, Wong EC, Yuen MF, Seto WK, Mak LY, Chan RW. Unmixing multi-spectral electrical impedance tomography (EIT) predicts clinical-standard controlled attenuation parameter (CAP) for nonalcoholic fatty liver disease classification: a feasibility study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:576-579. [PMID: 36086553 DOI: 10.1109/embc48229.2022.9871313] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Here, we tested the feasibility of predicting CAP with multi-spectral EIT. Conductivity and CAP were acquired from nonalcoholic fatty liver disease patients using a portable EIT system and vibration-controlled transient elastography (VCTE). We then used frequency-difference conductivity and waist-over-height as prediction features to estimate CAP and found an adj. R2 of 0.92. We further developed a novel prediction method by incorporating EIT spectral unmixing reconstruction and demonstrated an improvement in CAP estimation. Last, we optimized the EIT acquisition process by minimizing the total variance of the CAP estimator. Clinical Relevance: EIT can estimate clinical-standard liver disease classification. This portable EIT system is potentially cost-effective and self-administrable with short acquisition time (3 mins), while VCTE are costly and usually requires a trained personnel to operate with longer acquisition time (5-10 mins).
Collapse
|
5
|
Brazey B, Haddab Y, Zemiti N. Robust imaging using electrical impedance tomography: review of current tools. Proc Math Phys Eng Sci 2022; 478:20210713. [PMID: 35197802 PMCID: PMC8808710 DOI: 10.1098/rspa.2021.0713] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/13/2021] [Indexed: 01/26/2023] Open
Abstract
Electrical impedance tomography (EIT) is a medical imaging technique with many advantages and great potential for development in the coming years. Currently, some limitations of EIT are related to the ill-posed nature of the problem. These limitations are translated on a practical level by a lack of genericity of the developed tools. In this paper, the main robust data acquisition and processing tools for EIT proposed in the scientific literature are presented. Their relevance and potential to improve the robustness of EIT are analysed, in order to conclude on the feasibility of a robust EIT tool capable of providing resistivity or difference of resistivity mapping in a wide range of applications. In particular, it is shown that certain measurement acquisition tools and algorithms, such as faulty electrode detection algorithm or particular electrode designs, can ensure the quality of the acquisition in many circumstances. Many algorithms, aiming at processing acquired data, are also described and allow to overcome certain difficulties such as an error in the knowledge of the position of the boundaries or the poor conditioning of the inverse problem. They have a strong potential to faithfully reconstruct a quality image in the presence of disturbances such as noise or boundary modelling error.
Collapse
Affiliation(s)
| | | | - Nabil Zemiti
- LIRMM, Univ Montpellier, CNRS, Montpellier, France
| |
Collapse
|
6
|
Brazey B, Haddab Y, Koebel L, Zemiti N. Electrical impedance tomography: a potential tool for intraoperative imaging of the tongue base. Physiol Meas 2022; 43. [PMID: 35021162 DOI: 10.1088/1361-6579/ac4a87] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/12/2022] [Indexed: 11/12/2022]
Abstract
The presence of a tumor in the tongue is a pathology that requires surgical intervention from a certain stage. This type of surgery is difficult to perform because of the limited space available around the base of the tongue for the insertion of surgical tools. During the procedure, the surgeon has to stretch and then fix the tongue firmly in order to optimize the available space and prevent tissue movement. As a result, the preoperative images of the inside of the tongue no longer give a reliable indication of the position and shape of the cancerous tissue due to the deformation of the overall tissue in the area. Thus, new images are needed during the operation, but are very difficult to obtain using conventional techniques due to the presence of surgical tools. Electrical Impedance Tomography (EIT) is an imaging technique that maps the resistivity or difference of resistivity of biological tissues from electrical signals. The small size of the electrodes makes it a potentially interesting tool to obtain intraoperative images of the inside of the tongue. In this paper, the possibility of using EIT for this purpose is investigated. A detection method is proposed, including an original configuration of the electrodes, consistent with the anatomical specificities of the tongue. The proposed method is studied in simulation and then a proof of concept is obtained experimentally on a 3D printed test tank filled with saline solution and plant fibres.
Collapse
Affiliation(s)
- Benoit Brazey
- Robotics, LIRMM, 161 Rue Ada, Montpellier, Montpellier, 34000, FRANCE
| | - Yassine Haddab
- Robotics, LIRMM, 161 rue Ada, Montpellier, 34000, FRANCE
| | - Laure Koebel
- FEMTO-ST, 15B Av. des Montboucons, Besancon, Bourgogne-Franche-Comté, 25000, FRANCE
| | - Nabil Zemiti
- Robotics, LIRMM, 161 rue Ada, Montpellier, 34000, FRANCE
| |
Collapse
|
7
|
Chen R, Zhao S, Wu W, Sun Z, Wang J, Wang H, Han G. A convolutional neural network algorithm for breast tumor detection with magnetic detection electrical impedance tomography. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2021; 92:064701. [PMID: 34243519 DOI: 10.1063/5.0041423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of patients. Magnetic Detection Electrical Impedance Tomography (MDEIT) based on the Convolutional Neural Network (CNN), which aims to realize non-invasive, high resolution detection of breast tumors, is proposed. First, the MDEIT forward problem of the coronal and horizontal planes of the breast was simulated and solved using the Finite Element Method to obtain sample datasets of different lesions. Then, the CNN was built and trained to predict the conductivity distribution in different orientations of the breast model. Finally, noise and phantom experiments were performed in order to assess the anti-noise performance of the CNN algorithm and its feasibility of detecting breast tumors in practical applications. The simulation results showed that the reconstruction relative error with the CNN algorithm can be reduced to 10%, in comparison with the truncated singular value decomposition algorithm and back propagation algorithm. The CNN algorithm had better stability in the anti-noise performance test. When the noise of 60 dB was added, the shape of the breast tumor could still be restored by the CNN algorithm. The phantom experimental results showed that through the CNN based reconstruction algorithm, the reconstruction conductivity distribution image was legible and the position of the breast tumor could be determined. It is reasonable to conclude that the MDEIT reconstruction method proposed in this study has practical importance for the early and non-invasive detection of breast tumors.
Collapse
Affiliation(s)
- Ruijuan Chen
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Songsong Zhao
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Weiwei Wu
- School of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Zhihui Sun
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Jinhai Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Huiquan Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Guang Han
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| |
Collapse
|
8
|
Ogawa R, Baidillah MR, Akita S, Takei M. Investigation of Physiological Swelling on Conductivity Distribution in Lower Leg Subcutaneous Tissue by Electrical Impedance Tomography. JOURNAL OF ELECTRICAL BIOIMPEDANCE 2020; 11:19-25. [PMID: 33584899 PMCID: PMC7531098 DOI: 10.2478/joeb-2020-0004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Indexed: 06/12/2023]
Abstract
There is a strong need for a non-invasive measurement technique that is capable of accurately identifying the physiological condition change or heterogeneity of subcutaneous adipose tissue (SAT) by localizing the abnormalities within the compartment. This paper aims to investigate the feasibility of Electrical Impedance Tomography (EIT) to assess the interstitial fluid in subcutaneous adipose tissue as an enhancement method of bioelectrical impedance spectroscopy (BIS). Here, we demonstrate the preliminary result of EIT with a wearable 16 electrodes sensor. The image-based reference EIT with fat weighted threshold method is proposed. In order to evaluate the performance of our novel method, a physiological swelling experiment is conducted, and Multi-Frequency Bioelectrical Impedance Analysis (MFBIA) is also applied as a comparison with EIT results. The experimental results showed that the proposed method was able to distinguish the physiological swelling condition and effectively to remove the unexpected background noise. Furthermore, the conductivity variation in the subcutaneous layer had a good correlation with extracellular water volume change from MFBIA data; the correlation coefficient R2 = 0.927. It is concluded that the proposed method provides a significant prospect for SAT assessment.
Collapse
Affiliation(s)
- R. Ogawa
- Graduate School of Science & Eng., Dept. Mechanical Eng., Chiba University, Chiba, Japan
| | - M. R. Baidillah
- Graduate School of Science & Eng., Dept. Mechanical Eng., Chiba University, Chiba, Japan
| | - S. Akita
- Graduate School of Medicine, Dept. Reconstructive & Aesthetic Surgery, Chiba University, Chiba, Japan
| | - M. Takei
- Graduate School of Science & Eng., Dept. Mechanical Eng., Chiba University, Chiba, Japan
| |
Collapse
|
9
|
Cao L, Li H, Xu C, Dai M, Ji Z, Shi X, Dong X, Fu F, Yang B. A novel time-difference electrical impedance tomography algorithm using multi-frequency information. Biomed Eng Online 2019; 18:84. [PMID: 31358013 PMCID: PMC6664596 DOI: 10.1186/s12938-019-0703-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/20/2019] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Electrical impedance tomography (EIT) is a noninvasive, radiation-free, and low-cost imaging modality for monitoring the conductivity distribution inside a patient. Nowadays, time-difference EIT (tdEIT) is used extensively as it has fast imaging speed and can reflect the dynamic changes of diseases, which make it attractive for a number of medical applications. Moreover, modeling errors are compensated to some extent by subtraction of voltage measurements collected before and after the change. However, tissue conductivity varies with frequency and tdEIT does not efficiently exploit multi-frequency information as it only uses measurements associated with a single frequency. METHODS This paper proposes a tdEIT algorithm that imposes spectral constraints on the framework of the linear least squares problem. Simulation and phantom experiments are conducted to compare the proposed spectral constraints algorithm (SC) with the damped least squares algorithm (DLS), which is a stable tdEIT algorithm used in clinical practice. The condition number and rank of the matrices needing inverses are analyzed, and image quality is evaluated using four indexes. The possibility of multi-tissue imaging and the influence of spectral errors are also explored. RESULTS Significant performance improvement is achieved by combining multi-frequency and time-difference information. The simulation results show that, in one-step iteration, both algorithms have the same condition number and rank, but SC effectively reduces image noise by 20.25% compared to DLS. In addition, deformation error and position error are reduced by 8.37% and 7.86%, respectively. In two-step iteration, the rank of SC is greatly increased, which suggests that more information is employed in image reconstruction. Image noise is further reduced by an average of 32.58%, and deformation error and position error are also reduced by 20.20% and 31.36%, respectively. The phantom results also indicate that SC has stronger noise suppression and target identification abilities, and this advantage is more obvious with iteration. The results of multi-tissue imaging show that SC has the unique advantage of automatically extracting a single tissue to image. CONCLUSIONS SC enables tdEIT to utilize multi-frequency information in cases where the spectral constraints are known and then provides higher quality images for applications.
Collapse
Affiliation(s)
- Lu Cao
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Haoting Li
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Canhua Xu
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Meng Dai
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Zhenyu Ji
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Xuetao Shi
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Xiuzhen Dong
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Feng Fu
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| | - Bin Yang
- Department of Biomedical Engineering, Air Force Medical University (Fourth Military Medical University), Xi’an, 710032 People’s Republic of China
| |
Collapse
|
10
|
Nguyen DM, Qian P, Barry T, McEwan A. Self-weighted NOSER-prior electrical impedance tomography using internal electrodes in cardiac radiofrequency ablation. Physiol Meas 2019; 40:065006. [DOI: 10.1088/1361-6579/ab1937] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
11
|
Menden T, Orschulik J, Dambrun S, Matuszczyk J, Santos SA, Leonhardt S, Walter M. Reconstruction algorithm for frequency-differential EIT using absolute values. Physiol Meas 2019; 40:034008. [PMID: 30818291 DOI: 10.1088/1361-6579/ab0b55] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Tissues in the body differ by their frequency-dependent conductivity. Frequency-differential electrical impedance tomography (fdEIT) is a promising technique to reconstruct the distribution of tissue inside the body by injecting current at two frequencies and measuring the resulting surface-potential. APPROACH The Gauss-Newton method is one way to map the surface measurements to a conductivity image. Usually, the minimization function contains only weighted differential measurement data and a regularization. This traditional method is extended by absolute measurement data to improve fdEIT reconstruction results. The key challenge of unknown torso geometries and electrode displacement has been addressed for the reconstruction of different lung pathologies. MAIN RESULTS The frequency-dependent conductivity of the background was reconstructed precisely and a contrast between organs was achieved. The algorithm shows good performance compared to GREIT and the traditional Gauss-Newton method with respect to the figures of merit of GREIT. SIGNIFICANCE The reconstruction is robust in the presence of noise. One application of the algorithm might be the detection and monitoring of lung diseases like edema or atelectasis.
Collapse
Affiliation(s)
- Tobias Menden
- Medical Information Technology, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | | | | | | | | | | | | |
Collapse
|
12
|
Aguiar Santos S, Czaplik M, Orschulik J, Hochhausen N, Leonhardt S. Lung pathologies analyzed with multi-frequency electrical impedance tomography: Pilot animal study. Respir Physiol Neurobiol 2018; 254:1-9. [DOI: 10.1016/j.resp.2018.03.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 03/13/2018] [Accepted: 03/30/2018] [Indexed: 11/26/2022]
|
13
|
Xiao Z, Tan C, Dong F. Multi-frequency difference method for intracranial hemorrhage detection by magnetic induction tomography. Physiol Meas 2018; 39:055006. [PMID: 29701181 DOI: 10.1088/1361-6579/aac09c] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Frequency-difference magnetic induction tomography (fdMIT) is a promising technique for the continuous monitoring of intracranial hemorrhage. The dual-frequency difference MIT (dfdMIT) will sometimes produce artefacts in the reconstructed images. To overcome this problem, a multi-frequency difference MIT (mfdMIT) method is proposed. APPROACH To test the performance of this algorithm, 2D head models comprising six tissue types with different hemorrhage sizes were simulated, and images of the hemorrhage were reconstructed by mfdMIT and dfdMIT. Imaging errors and correlation coefficients were calculated with different levels of added phase noise and conductivity noise. MAIN RESULTS A hemorrhage with a diameter of 20 mm can be reconstructed with 20 dB noise by the mfdMIT method, and the imaging error is reduced by about 60%. The results show that the conductivity of brain tissues changing with frequency will cause artefacts on the reconstructed images of the hemorrhage by dfdMIT, but the artefacts can be effectively suppressed with mfdMIT by separating the hemorrhage from other brain tissues. SIGNIFICANCE The mfdMIT method increases the reconstructed image precision, which promotes the development of medical imaging by MIT.
Collapse
Affiliation(s)
- Zhili Xiao
- Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin, People's Republic of China
| | | | | |
Collapse
|
14
|
Orschulik J, Hochhausen N, Czaplik M, Teichmann D, Leonhardt S, Walter M. Addition of internal electrodes is beneficial for focused bioimpedance measurements in the lung. Physiol Meas 2018; 39:035009. [PMID: 29406309 DOI: 10.1088/1361-6579/aaad45] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Bioimpedance measurements such as bioimpedance spectroscopy (BIS) or electrical impedance tomography (EIT) are used in many biomedical applications. While BIS measures and analyzes the impedance in a frequency range at constant electrode positions, EIT aims to reconstruct images of the conductivity distribution from multiple measurements at different electrode positions. Our aim is to add spatial information to tetrapolar BIS measurements by using electrode positions that focus measurements on desired regions of interest. In this paper, we aim to investigate, whether internal electrodes that can be integrated into breathing or gastroesophageal tubes, can improve the local sensitivity of bioimpedance spectroscopy measurements. APPROACH We present the results of a simulation study, in which we investigated more than 4 M different electrode configurations on their ability to monitor specific regions of interest (ROI) in the lung. Based on the sensitivity, which describes the impact of a conductivity change on the measured impedance, we define three main criteria which we use to evaluate our simulation results: the selectivity [Formula: see text], which describes the impact of a conductivity change inside the region of interest compared to a conductivity change outside the ROI; the homogeneity [Formula: see text], which describes the distribution of the sensitivity inside the ROI; and the absolute impedance contribution ratio [Formula: see text], which describes the contribution of the ROI to the measured impedance. MAIN RESULTS Depending on the region of interest, electrode configurations using internal electrodes are between 9.8 % and 90 % better with respect to these criteria than configurations using external electrodes only. SIGNIFICANCE The combination of internal and external electrodes improves the focusing ability of tetrapolar impedance measurements on specific lung regions, which may be especially beneficial for lung monitoring in intensive care.
Collapse
Affiliation(s)
- Jakob Orschulik
- Philips Chair for Medical Information Technology, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | | | | | | | | | | |
Collapse
|
15
|
Han B, Xu Y, Dong F. Design of current source for multi-frequency simultaneous electrical impedance tomography. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2017; 88:094709. [PMID: 28964244 DOI: 10.1063/1.5004185] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 09/11/2017] [Indexed: 06/07/2023]
Abstract
Multi-frequency electrical impedance tomography has been evolving from the frequency-sweep approach to the multi-frequency simultaneous measurement technique which can reduce measuring time and will be increasingly attractive for time-varying biological applications. The accuracy and stability of the current source are the key factors determining the quality of the image reconstruction. This article presents a field programmable gate array-based current source for a multi-frequency simultaneous electrical impedance tomography system. A novel current source circuit was realized by combining the classic current mirror based on the feedback amplifier AD844 with a differential topology. The optimal phase offsets of harmonic sinusoids were obtained through the crest factor analysis. The output characteristics of this current source were evaluated by simulation and actual measurement. The results include the following: (1) the output impedance was compared with one of the Howland pump circuit in simulation, showing comparable performance at low frequencies. However, the proposed current source makes lower demands for resistor tolerance but performs even better at high frequencies. (2) The output impedance in actual measurement below 200 kHz is above 1.3 MΩ and can reach 250 KΩ up to 1 MHz. (3) An experiment based on a biological RC model has been implemented. The mean error for the demodulated impedance amplitude and phase are 0.192% and 0.139°, respectively. Therefore, the proposed current source is wideband, biocompatible, and high precision, which demonstrates great potential to work as a sub-system in the multi-frequency electrical impedance tomography system.
Collapse
Affiliation(s)
- Bing Han
- Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin, People's Republic of China
| | - Yanbin Xu
- Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin, People's Republic of China
| | - Feng Dong
- Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin, People's Republic of China
| |
Collapse
|
16
|
Yang L, Dai M, Xu C, Zhang G, Li W, Fu F, Shi X, Dong X. The Frequency Spectral Properties of Electrode-Skin Contact Impedance on Human Head and Its Frequency-Dependent Effects on Frequency-Difference EIT in Stroke Detection from 10Hz to 1MHz. PLoS One 2017; 12:e0170563. [PMID: 28107524 PMCID: PMC5249181 DOI: 10.1371/journal.pone.0170563] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 01/08/2017] [Indexed: 11/18/2022] Open
Abstract
Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects’ heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection.
Collapse
Affiliation(s)
- Lin Yang
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Meng Dai
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Canhua Xu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Ge Zhang
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Weichen Li
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Feng Fu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Xuetao Shi
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Xiuzhen Dong
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| |
Collapse
|
17
|
Yang L, Xu C, Dai M, Fu F, Shi X, Dong X. A novel multi-frequency electrical impedance tomography spectral imaging algorithm for early stroke detection. Physiol Meas 2016; 37:2317-2335. [PMID: 27897152 DOI: 10.1088/1361-6579/37/12/2317] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Multi-frequency electrical impedance tomography (MFEIT) reconstructs the image of conductivity inside the human body based on the dependence of tissue conductivity on frequency. As there exist differences in the conductivity over frequency between blood, ischemic cortical tissue and normal cortical tissue, MFEIT has potential application in the detection of acute stroke. However, because the conductivity distribution of the human head is highly inhomogeneous and the conductivities of normal head tissue and stroke lesion tissue both change with frequency, the anomaly and normal head tissues are often mixed together in the reconstructed image, which makes it difficult to discern the anomaly. Here we present a spectral decomposition frequency-difference (SD-FD) imaging algorithm in an attempt to address this issue: firstly, we reconstruct so-called EIT spectral images according to the conductivity spectra of tissues; secondly, we obtain the EIT image of the anomaly from the spectral images by using independent component analysis. The results show that the proposed algorithm is capable of detecting the anomaly in a numerical head phantom, as well as in a realistic human head tank with frequency-dependent and heterogeneous conductivities distribution. The proposed SD-FD algorithm may support MFEIT use for human stroke imaging in the future.
Collapse
|
18
|
System Description and First Application of an FPGA-Based Simultaneous Multi-Frequency Electrical Impedance Tomography. SENSORS 2016; 16:s16081158. [PMID: 27463715 PMCID: PMC5017324 DOI: 10.3390/s16081158] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Revised: 06/02/2016] [Accepted: 07/21/2016] [Indexed: 11/16/2022]
Abstract
A new prototype of a multi-frequency electrical impedance tomography system is presented. The system uses a field-programmable gate array as a main controller and is configured to measure at different frequencies simultaneously through a composite waveform. Both real and imaginary components of the data are computed for each frequency and sent to the personal computer over an ethernet connection, where both time-difference imaging and frequency-difference imaging are reconstructed and visualized. The system has been tested for both time-difference and frequency-difference imaging for diverse sets of frequency pairs in a resistive/capacitive test unit and in self-experiments. To our knowledge, this is the first work that shows preliminary frequency-difference images of in-vivo experiments. Results of time-difference imaging were compared with simulation results and shown that the new prototype performs well at all frequencies in the tested range of 60 kHz-960 kHz. For frequency-difference images, further development of algorithms and an improved normalization process is required to correctly reconstruct and interpreted the resulting images.
Collapse
|
19
|
Jehl M, Holder D. Correction of electrode modelling errors in multi-frequency EIT imaging. Physiol Meas 2016; 37:893-903. [PMID: 27206237 DOI: 10.1088/0967-3334/37/6/893] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The differentiation of haemorrhagic from ischaemic stroke using electrical impedance tomography (EIT) requires measurements at multiple frequencies, since the general lack of healthy measurements on the same patient excludes time-difference imaging methods. It has previously been shown that the inaccurate modelling of electrodes constitutes one of the largest sources of image artefacts in non-linear multi-frequency EIT applications. To address this issue, we augmented the conductivity Jacobian matrix with a Jacobian matrix with respect to electrode movement. Using this new algorithm, simulated ischaemic and haemorrhagic strokes in a realistic head model were reconstructed for varying degrees of electrode position errors. The simultaneous recovery of conductivity spectra and electrode positions removed most artefacts caused by inaccurately modelled electrodes. Reconstructions were stable for electrode position errors of up to 1.5 mm standard deviation along both surface dimensions. We conclude that this method can be used for electrode model correction in multi-frequency EIT.
Collapse
Affiliation(s)
- Markus Jehl
- University College London, London WC1E 6BT, UK
| | | |
Collapse
|
20
|
Jehl M, Avery J, Malone E, Holder D, Betcke T. Correcting electrode modelling errors in EIT on realistic 3D head models. Physiol Meas 2015; 36:2423-42. [PMID: 26502162 DOI: 10.1088/0967-3334/36/12/2423] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Electrical impedance tomography (EIT) is a promising medical imaging technique which could aid differentiation of haemorrhagic from ischaemic stroke in an ambulance. One challenge in EIT is the ill-posed nature of the image reconstruction, i.e., that small measurement or modelling errors can result in large image artefacts. It is therefore important that reconstruction algorithms are improved with regard to stability to modelling errors. We identify that wrongly modelled electrode positions constitute one of the biggest sources of image artefacts in head EIT. Therefore, the use of the Fréchet derivative on the electrode boundaries in a realistic three-dimensional head model is investigated, in order to reconstruct electrode movements simultaneously to conductivity changes. We show a fast implementation and analyse the performance of electrode position reconstructions in time-difference and absolute imaging for simulated and experimental voltages. Reconstructing the electrode positions and conductivities simultaneously increased the image quality significantly in the presence of electrode movement.
Collapse
Affiliation(s)
- Markus Jehl
- University College London, London WC1E 6BT, UK
| | | | | | | | | |
Collapse
|
21
|
Zhou Z, Dowrick T, Malone E, Avery J, Li N, Sun Z, Xu H, Holder D. Multifrequency electrical impedance tomography with total variation regularization. Physiol Meas 2015; 36:1943-61. [PMID: 26245292 DOI: 10.1088/0967-3334/36/9/1943] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Multifrequency electrical impedance tomography (MFEIT) reconstructs the distribution of conductivity by exploiting the dependence of tissue conductivity on frequency. MFEIT can be performed on a single instance of data, making it promising for applications such as stroke and cancer imaging, where it is not possible to obtain a 'baseline' measurement of healthy tissue. A nonlinear MFEIT algorithm able to reconstruct the volume fraction distribution of tissue rather than conductivities has been developed previously. For each volume, the fraction of a certain tissue should be either 1 or 0; this implies that the sharp changes of the fractions, representing the boundaries of tissue, contain all the relevant information. However, these boundaries are blurred by traditional regularization methods using [Formula: see text] norm. The total variation (TV) regularization can overcome this problem, but it is difficult to solve due to its non-differentiability. Because the fraction must be between 0 and 1, this imposes a constraint on the MFEIT method based on the fraction model. Therefore, a constrained optimization method capable of dealing with non-differentiable problems is required. Based on the primal and dual interior point method, we propose a new constrained TV regularized method to solve the fraction reconstruction problem. The noise performance of the new MFEIT method is analysed using simulations on a 2D cylindrical mesh. Convergence performance is also analysed through experiments using a cylindrical tank. Finally, simulations on an anatomically realistic head-shaped mesh are demonstrated. The proposed MFEIT method with TV regularization shows higher spatial resolution, particularly at the edges of the perturbation, and stronger noise robustness, and its image noise and shape error are 20% to 30% lower than the traditional fraction method.
Collapse
Affiliation(s)
- Zhou Zhou
- National University of Defense Technology, Changsha, 410073, People's Republic of China. University College London, London, WC1E 6BT, UK
| | | | | | | | | | | | | | | |
Collapse
|
22
|
Malone E, Sato Dos Santos G, Holder D, Arridge S. A Reconstruction-Classification Method for Multifrequency Electrical Impedance Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:1486-1497. [PMID: 25680206 DOI: 10.1109/tmi.2015.2402661] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Multifrequency Electrical Impedance Tomography is an imaging technique which distinguishes biological tissues by their unique conductivity spectrum. Recent results suggest that the use of spectral constraints can significantly improve image quality. We present a combined reconstruction-classification method for estimating the spectra of individual tissues, whilst simultaneously reconstructing the conductivity. The advantage of this method is that a priori knowledge of the spectra is not required to be exact in that the constraints are updated at each step of the reconstruction. In this paper, we investigate the robustness of the proposed method to errors in the initial guess of the tissue spectra, and look at the effect of introducing spatial smoothing. We formalize and validate a frequency-difference variant of reconstruction-classification, and compare the use of absolute and frequency-difference data in the case of a phantom experiment.
Collapse
|
23
|
Jang J, Seo JK. Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT. Physiol Meas 2015; 36:1179-92. [PMID: 26008619 DOI: 10.1088/0967-3334/36/6/1179] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.
Collapse
Affiliation(s)
- J Jang
- Computational Science and Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Korea
| | | |
Collapse
|
24
|
Wi H, McEwan AL, Lam V, Kim HJ, Woo EJ, Oh TI. Real-time conductivity imaging of temperature and tissue property changes during radiofrequency ablation: An ex vivo model using weighted frequency difference. Bioelectromagnetics 2015; 36:277-86. [DOI: 10.1002/bem.21904] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2014] [Accepted: 02/05/2015] [Indexed: 02/01/2023]
Affiliation(s)
- Hun Wi
- Department of Biomedical Engineering; Kyung Hee University; Yongin Korea
- Department of Computational Science and Engineering; Yonsei University; Seoul Korea
| | - Alistair Lee McEwan
- Department of Biomedical Engineering; Kyung Hee University; Yongin Korea
- The School of Electrical and Information Engineering; The University of Sydney; Sydney Australia
| | - Vincent Lam
- Faculty of Medicine; The University of Sydney; Sydney Australia
| | - Hyung Joong Kim
- Department of Biomedical Engineering; Kyung Hee University; Yongin Korea
| | - Eung Je Woo
- Department of Biomedical Engineering; Kyung Hee University; Yongin Korea
| | - Tong In Oh
- Department of Biomedical Engineering; Kyung Hee University; Yongin Korea
| |
Collapse
|
25
|
Abstract
An instrumental electrode model (IEM) capable of describing the performance of electrical impedance tomography (EIT) systems in the MHz frequency range has been proposed. Compared with the commonly used Complete Electrode Model (CEM), which assumes ideal front-end interfaces, the proposed model considers the effects of non-ideal components in the front-end circuits. This introduces an extra boundary condition in the forward model and offers a more accurate modelling for EIT systems. We have demonstrated its performance using simple geometry structures and compared the results with the CEM and full Maxwell methods. The IEM can provide a significantly more accurate approximation than the CEM in the MHz frequency range, where the full Maxwell methods are favoured over the quasi-static approximation. The improved electrode model will facilitate the future characterization and front-end design of real-world EIT systems.
Collapse
Affiliation(s)
- Weida Zhang
- Department of Engineering and Design, School of Engineering and Informatics, University of Sussex, BN1 9SB, UK. Department of Electronic Engineering, School of Information and Electronics, Beijing Institute of Technology, 100081, People's Republic of China
| | | |
Collapse
|
26
|
Exploratory study on the methodology of fast imaging of unilateral stroke lesions by electrical impedance asymmetry in human heads. ScientificWorldJournal 2014; 2014:534012. [PMID: 25006594 PMCID: PMC4060593 DOI: 10.1155/2014/534012] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 04/09/2014] [Indexed: 11/29/2022] Open
Abstract
Stroke has a high mortality and disability rate and should be rapidly diagnosed to improve prognosis. Diagnosing stroke is not a problem for hospitals with CT, MRI, and other imaging devices but is difficult for community hospitals without these devices. Based on the mechanism that the electrical impedance of the two hemispheres of a normal human head is basically symmetrical and a stroke can alter this symmetry, a fast electrical impedance imaging method called symmetrical electrical impedance tomography (SEIT) is proposed. In this technique, electrical impedance tomography (EIT) data measured from the undamaged craniocerebral hemisphere (CCH) is regarded as reference data for the remaining EIT data measured from the other CCH for difference imaging to identify the differences in resistivity distribution between the two CCHs. The results of SEIT imaging based on simulation data from the 2D human head finite element model and that from the physical phantom of human head verified this method in detection of unilateral stroke.
Collapse
|
27
|
Malone E, Sato Dos Santos G, Holder D, Arridge S. Multifrequency electrical impedance tomography using spectral constraints. IEEE TRANSACTIONS ON MEDICAL IMAGING 2014; 33:340-350. [PMID: 24122550 DOI: 10.1109/tmi.2013.2284966] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Multifrequency electrical impedance tomography (MFEIT) exploits the dependence of tissue impedance on frequency to recover an image of conductivity. MFEIT could provide emergency diagnosis of pathologies such as acute stroke, brain injury and breast cancer. We present a method for performing MFEIT using spectral constraints. Boundary voltage data is employed directly to reconstruct the volume fraction distribution of component tissues using a nonlinear method. Given that the reconstructed parameter is frequency independent, this approach allows for the simultaneous use of all multifrequency data, thus reducing the degrees of freedom of the reconstruction problem. Furthermore, this method allows for the use of frequency difference data in a nonlinear reconstruction algorithm. Results from empirical phantom measurements suggest that our fraction reconstruction method points to a new direction for the development of multifrequency EIT algorithms in the case that the spectral constraints are known, and may provide a unifying framework for static EIT imaging.
Collapse
|
28
|
Kwon H, McEwan AL, Oh TI, Farooq A, Woo EJ, Seo JK. A local region of interest imaging method for electrical impedance tomography with internal electrodes. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2013; 2013:964918. [PMID: 23935705 PMCID: PMC3722843 DOI: 10.1155/2013/964918] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2012] [Revised: 06/01/2013] [Accepted: 06/10/2013] [Indexed: 11/18/2022]
Abstract
Electrical Impedance Tomography (EIT) is a very attractive functional imaging method despite the low sensitivity and resolution. The use of internal electrodes with the conventional reconstruction algorithms was not enough to enhance image resolution and accuracy in the region of interest (ROI). We propose a local ROI imaging method with internal electrodes developed from careful analysis of the sensitivity matrix that is designed to reduce the sensitivity of the voxels outside the local region and optimize the sensitivity of the voxel inside the local region. We perform numerical simulations and physical measurements to demonstrate the localized EIT imaging method. In preliminary results with multiple objects we show the benefits of using an internal electrode and the improved resolution due to the local ROI image reconstruction method. The sensitivity is further increased by allowing the surface electrodes to be unevenly spaced with a higher density of surface electrodes near the ROI. Also, we analyse how much the image quality is improved using several performance parameters for comparison. While these have not yet been studied in depth, it convincingly shows an improvement in local sensitivity in images obtained with an internal electrode in comparison to a standard reconstruction method.
Collapse
Affiliation(s)
- Hyeuknam Kwon
- Department of Computational Science and Engineering, Yonsei University, Seoul 120-749, Republic of Korea
| | - Alistair L. McEwan
- The School of Electrical and Information Engineering, The University of Sydney, Sydney NSW 2006, Australia
- Impedance Imaging Research Center and Department of Biomedical Engineering, Kyung Hee University, Yongin 446-701, Republic of Korea
| | - Tong In Oh
- Impedance Imaging Research Center and Department of Biomedical Engineering, Kyung Hee University, Yongin 446-701, Republic of Korea
| | - Adnan Farooq
- Impedance Imaging Research Center and Department of Biomedical Engineering, Kyung Hee University, Yongin 446-701, Republic of Korea
| | - Eung Je Woo
- Impedance Imaging Research Center and Department of Biomedical Engineering, Kyung Hee University, Yongin 446-701, Republic of Korea
| | - Jin Keun Seo
- Department of Computational Science and Engineering, Yonsei University, Seoul 120-749, Republic of Korea
| |
Collapse
|
29
|
Zhao M, Wi H, Mostofa Kamal AH, McEwan AL, Woo EJ, Oh TI. High density trans-admittance mammography development and preliminary phantom tests. Biomed Eng Online 2012; 11:75. [PMID: 23009288 PMCID: PMC3537578 DOI: 10.1186/1475-925x-11-75] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2012] [Accepted: 09/05/2012] [Indexed: 11/29/2022] Open
Abstract
Background Malignant breast tumor tissue has a significantly different electrical impedance spectrum than surrounding normal tissues. This has led to the development of impedance imaging as a supplementary or alternative method to X-ray mammography for screening and assessment of breast cancers. However low spatial resolution and poor signal to noise ratio has limited the clinical application. Methods In order to improve spatial resolution we developed a trans-admittance mammography (TAM) system including an array of 60×60 current sensing electrodes. We adopted a similar setup to X-ray mammography where the breast is situated between two holding plates. The top plate is a large solid metal electrode for applying a sinusoidal voltage over a range of frequencies from 50 Hz to 500 kHz. The bottom plate has 3600 current sensing electrodes that are kept at the ground potential. Currents are generated from the top voltage-applying electrode and spread throughout the breast, entering the TAM system through the array of current sensing electrodes on the bottom plate. The TAM system measures the exit currents through 6 switching modules connected to 600 electrodes each. Each switching module is connected to 12 ammeter channels which are switched sequentially to 50 of the 600 electrodes each measurement time. Each ammeter channel is comprised of a current-to-voltage converter, a gain amplifier, filters, an analog to digital converter, and a digital phase sensitive demodulator. Results We found an average noise level of 38 nA, amplitude stability of less than 0.2%, crosstalk of better than -60 dB and 70 dB signal to noise ratio over all channels and operating frequencies. Images were obtained in time difference and frequency difference modes in a saline phantom. Conclusion We describe the design, construction, and calibration of a high density TAM system in detail. Successful high resolution time and frequency difference images showed regions of interest with the expected admittivity changes in the frequency spectrum.
Collapse
Affiliation(s)
- Mingkang Zhao
- Department of Biomedical Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do 446-701, Korea
| | | | | | | | | | | |
Collapse
|
30
|
Lee E, Ts ME, Seo JK, Woo EJ. Breast EIT using a new projected image reconstruction method with multi-frequency measurements. Physiol Meas 2012; 33:751-65. [PMID: 22532397 DOI: 10.1088/0967-3334/33/5/751] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
We propose a new method to produce admittivity images of the breast for the diagnosis of breast cancer using electrical impedance tomography(EIT). Considering the anatomical structure of the breast, we designed an electrode configuration where current-injection and voltage-sensing electrodes are separated in such a way that internal current pathways are approximately along the tangential direction of an array of voltage-sensing electrodes. Unlike conventional EIT imaging methods where the number of injected currents is maximized to increase the total amount of measured data, current is injected only twice between two pairs of current-injection electrodes attached along the circumferential side of the breast. For each current injection, the induced voltages are measured from the front surface of the breast using as many voltage-sensing electrodes as possible. Although this electrode configurational lows us to measure induced voltages only on the front surface of the breast,they are more sensitive to an anomaly inside the breast since such an injected current tends to produce a more uniform internal current density distribution. Furthermore, the sensitivity of a measured boundary voltage between two equipotential lines on the front surface of the breast is improved since those equipotential lines are perpendicular to the primary direction of internal current streamlines. One should note that this novel data collection method is different from those of other frontal plane techniques such as the x-ray projection and T-scan imaging methods because we do not get any data on the plane that is perpendicular to the current flow. To reconstruct admittivity images using two measured voltage data sets, a new projected image reconstruction algorithm is developed. Numerical simulations demonstrate the frequency-difference EIT imaging of the breast. The results show that the new method is promising to accurately detect and localize small anomalies inside the breast.
Collapse
Affiliation(s)
- Eunjung Lee
- Department of Computational Science and Engineering, Yonsei University, Seoul, Korea.
| | | | | | | |
Collapse
|
31
|
Packham B, Koo H, Romsauerova A, Ahn S, McEwan A, Jun SC, Holder DS. Comparison of frequency difference reconstruction algorithms for the detection of acute stroke using EIT in a realistic head-shaped tank. Physiol Meas 2012; 33:767-86. [PMID: 22531059 DOI: 10.1088/0967-3334/33/5/767] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Imaging of acute stroke might be possible using multi-frequency electrical impedance tomography (MFEIT) but requires absolute or frequency difference imaging. Simple linear frequency difference reconstruction has been shown to be ineffective in imaging with a frequency-dependant background conductivity; this has been overcome with a weighted frequency difference approach with correction for the background but this has only been validated for a cylindrical and hemispherical tank. The feasibility of MFEIT for imaging of acute stroke in a realistic head geometry was examined by imaging a potato perturbation against a saline background and a carrot-saline frequency-dependant background conductivity, in a head-shaped tank with the UCLH Mk2.5 MFEIT system. Reconstruction was performed with time difference (TD), frequency difference (FD), FD adjacent (FDA), weighted FD (WFD) and weighted FDA (WFDA) linear algorithms. The perturbation in reconstructed images corresponded to the true position to <9.5% of image diameter with an image SNR of >5.4 for all algorithms in saline but only for TD, WFDA and WFD in the carrot-saline background. No reliable imaging was possible with FD and FDA. This indicates that the WFD approach is also effective for a realistic head geometry and supports its use for human imaging in the future.
Collapse
Affiliation(s)
- B Packham
- Department of Medical Physics and Bioengineering, UCL, London, UK.
| | | | | | | | | | | | | |
Collapse
|
32
|
Ahn S, Oh TI, Jun SC, Seo JK, Woo EJ. Validation of weighted frequency-difference EIT using a three-dimensional hemisphere model and phantom. Physiol Meas 2011; 32:1663-80. [PMID: 21904022 DOI: 10.1088/0967-3334/32/10/013] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Frequency-difference (FD) electrical impedance tomography (EIT) using a weighted voltage difference has recently been proposed for imaging haemorrhagic stroke, abdominal bleeding and tumors. Although its feasibility was demonstrated through two-dimensional numerical simulations and phantom experiments, we should validate the method in three-dimensional imaging objects. At the same time, we need to investigate its robustness against geometrical modeling errors in boundary shapes and electrode positions. We performed a validation study of the weighted FD method through three-dimensional numerical simulations and phantom experiments. Adopting hemispherical models and phantoms whose admittivity distributions change with frequency, we investigated the performance of the method to detect an anomaly. We found that the simple FD method fails to detect the anomaly, whereas reconstructed images using the weighted FD method clearly visualize the anomaly. The weighted FD method is robust against modeling errors of boundary-shape deformations and displaced electrode positions. We also found that the method is capable of detecting an anomaly surrounded by a shell-shaped obstacle simulating the skull. We propose the weighted FD method for future studies of animal and human experiments.
Collapse
Affiliation(s)
- Sujin Ahn
- School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Korea
| | | | | | | | | |
Collapse
|
33
|
Oh TI, Wi H, Kim DY, Yoo PJ, Woo EJ. A fully parallel multi-frequency EIT system with flexible electrode configuration: KHU Mark2. Physiol Meas 2011; 32:835-49. [DOI: 10.1088/0967-3334/32/7/s08] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
34
|
Harrach B, Seo JK, Woo EJ. Factorization method and its physical justification in frequency-difference electrical impedance tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2010; 29:1918-1926. [PMID: 20570764 DOI: 10.1109/tmi.2010.2053553] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Time-difference electrical impedance tomography (tdEIT) requires two data sets measured at two different times. The difference between them is utilized to produce images of time-dependent changes in a complex conductivity distribution inside the human body. Frequency-difference EIT (fdEIT) was proposed to image frequency-dependent changes of a complex conductivity distribution. It has potential applications in tumor and stroke imaging since it can visualize an anomaly without requiring any time-reference data obtained in the absence of an anomaly. In this paper, we provide a rigorous analysis for the detectability of an anomaly based on a constructive and quantitative physical correlation between a measured fdEIT data set and an anomaly. From this, we propose a new noniterative frequency-difference anomaly detection method called the factorization method (FM) and elaborate its physical justification. To demonstrate its practical applicability, we performed fdEIT phantom imaging experiments using a multifrequency EIT system. Applying the FM to measured frequency-difference boundary voltage data sets, we could quantitatively evaluate indicator functions inside the imaging domain, of which values at each position reveal presence or absence of an anomaly. We found that the FM successfully localizes anomalies inside an imaging domain with a frequency-dependent complex conductivity distribution. We propose the new FM as an anomaly detection algorithm in fdEIT for potential applications in tumor and stroke imaging.
Collapse
Affiliation(s)
- Bastian Harrach
- Fakultät für Mathematik, Technische Universität München, 85748 Garching, Germany.
| | | | | |
Collapse
|
35
|
Ahn S, Oh TI, Jun SC, Lee J, Seo JK, Woo EJ. Weighted frequency-difference EIT measurement of hemisphere phantom. ACTA ACUST UNITED AC 2010. [DOI: 10.1088/1742-6596/224/1/012059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|