Electrical Impedance Tomography reconstruction using l1 norms for data and image terms.

نویسندگان

  • Tao Dai
  • Andy Adler
چکیده

Electrical Impedance Tomography (EIT) calculates the internal conductivity distribution within a body from current simulation and voltage measurements on the body surface. Two main technical difficulties of EIT are its low spatial resolution and sensitivity to measurement errors. Image reconstruction using l(1) norms allows addressing both difficulties, in comparison to traditional reconstruction using l(2) norms. A l(1) norm on the data residue term reduces the sensitivity to measurement errors, while the l(1) norm on the image prior reduces edge blurring. This paper proposes and tests a general lagged diffusivity type iterative method for EIT reconstructions l(1) and l(2) minimizations can be flexibly chosen on the data residue and/or image prior parts. Results show the flexibility of the algorithm and the merits of the l(1) solution.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Level Set based Regularization Framework for EIT Image Reconstruction

Electrical Impedance Tomography (EIT) reconstructs the conductivity distribution within a medium from electrical stimulation and measurements at the medium surface. Level set based reconstruction method (LSRM) has gained attention during the last decade as an effective solution to address the need of reconstructing structures with limited amount of available data. The classical LSRM is based on...

متن کامل

Experimental / clinical evaluation of EIT image reconstruction with l 1 data and image norms

Electrical impedance tomography (EIT) image reconstruction is ill-posed, and the spatial resolution of reconstructed images is low due to the diffuse propagation of current and limited number of independent measurements. Generally, image reconstruction is formulated using a regularized scheme in which `2 norms are preferred for both the data misfit and image prior terms due to computational con...

متن کامل

A Primal Dual Interior Point Framework for EIT Reconstruction with Automatic Regularization

The spatial resolution of the reconstructed images in Electrical impedance tomography (EIT) is low and a priori information regarding smooth conductivity changes limits reconstruction of sharp images while it is preferred in order to differentiate tissue boundaries in medical imaging. Measurement errors are another barrier that hinder a good image reconstruction. Generally `2 norms have been us...

متن کامل

Temporal image reconstruction in electrical impedance tomography.

Electrical impedance tomography (EIT) calculates images of the body from body impedance measurements. While the spatial resolution of these images is relatively low, the temporal resolution of EIT data can be high. Most EIT reconstruction algorithms solve each data frame independently, although Kalman filter algorithms track the image changes across frames. This paper proposes a new approach wh...

متن کامل

Using real data to train GREIT improves image quality

Image reconstruction in electrical impedance tomography is sensitive to errors in the (forward) model of the measurement system. We propose a new approach, based on the GREIT algorithm, where the reconstruction matrix is trained on real rather than simulated data, obviating the need for an accurate numerical forward model. We observe a substantial improvement in image quality, particularly for ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

دوره 2008  شماره 

صفحات  -

تاریخ انتشار 2008