DocumentCode
3303867
Title
EIT in Breast Cancer Imaging: Application to Patient-Specific Forward Model
Author
Abdi, Montaserbellah ; Liatsis, Panos
Author_Institution
Sch. of Eng. & Math. Sci., City Univ. London, London, UK
fYear
2011
fDate
6-8 Dec. 2011
Firstpage
56
Lastpage
61
Abstract
Electrical Impedance Tomography is a relatively new technique whereby objects or phantoms can be imaged through injecting the containing medium with electrical currents along its periphery. EIT, in its various forms, has been applied to several areas in medical diagnosis and monitoring, including the measurements of breast tissues impedance. Studies have shown that cancerous tissues have electrical properties that are significantly different from their normal surroundings. X-ray mammography has been set as the primary method of breast cancer screening. However, EIT currently still falls within a category of techniques which are used as adjunct methods to X-ray mammography, in this category are Ultrasound and MRI. These techniques are used as follow-up on the results of mammography. the problem of estimating the inner conductivities from surface measurements is an ill-conditioned problem in which some regularization strategies have to take place in order to obtain a stable and accurate solution by incorporating some prior information into the solution. the purpose of this paper is to demonstrate the application of EIT on a patient-specific model for the single- and multiple-electrodes models and discuss the pros and cons of adding dimensionality to the model with respect to the image reconstruction process. This comparison will be based on the RMSE (Root mean square error) and Pearson´s correlation criteria which were not used previously in this respect.
Keywords
cancer; electric impedance imaging; image reconstruction; mean square error methods; medical image processing; EIT; Pearson correlation; RMSE; X-ray mammography; breast cancer imaging; breast cancer screening; breast tissue impedance; electrical current; electrical impedance tomography; electrical properties; image reconstruction; patient-specific forward model; root mean square error; Breast cancer; Computational modeling; Conductivity; Electrodes; Image reconstruction; Tomography; Electrical impedance tomography; L-curve; Tikhonov regularisation; breast cancer; dual models.; finite element method; hyperparameter;
fLanguage
English
Publisher
ieee
Conference_Titel
Developments in E-systems Engineering (DeSE), 2011
Conference_Location
Dubai
Print_ISBN
978-1-4577-2186-1
Type
conf
DOI
10.1109/DeSE.2011.98
Filename
6149955
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