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Tomography

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Improved Imaging Resolution of Electrical Impedance Tomography Using Artificial Neural Networks for Image Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electrical impedance tomography (EIT) is a noninvasive and non-radiative medical imaging technique based on detecting the inhomogeneous electrical properties of the tissue. The inverse problem of EIT is a highly nonlinear ill-posed problem, which is ...

Combining deep learning and 3D contrast source inversion in MR-based electrical properties tomography.

NMR in biomedicine
Magnetic resonance electrical properties tomography (MR-EPT) is a technique used to estimate the conductivity and permittivity of tissues from MR measurements of the transmit magnetic field. Different reconstruction methods are available; however, al...

Electrical Impedance Tomography-Based Abdominal Subcutaneous Fat Estimation Method Using Deep Learning.

Computational and mathematical methods in medicine
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...

An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

IEEE transactions on biomedical circuits and systems
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...

Artificial Intelligence in Multiphoton Tomography: Atopic Dermatitis Diagnosis.

Scientific reports
The diagnostic possibilities of multiphoton tomography (MPT) in dermatology have already been demonstrated. Nevertheless, the analysis of MPT data is still time-consuming and operator dependent. We propose a fully automatic approach based on convolut...

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...

Multi-frequency symmetry difference electrical impedance tomography with machine learning for human stroke diagnosis.

Physiological measurement
OBJECTIVE: Multi-frequency symmetry difference electrical impedance tomography (MFSD-EIT) can robustly detect and identify unilateral perturbations in symmetric scenes. Here, an investigation is performed to assess if the algorithm can be successfull...

Neural network-based supervised descent method for 2D electrical impedance tomography.

Physiological measurement
OBJECTIVE: In this work, we study the application of the neural network-based supervised descent method (NN-SDM) for 2D electrical impedance tomography.

Deep Neural Network-Based Sinogram Super-Resolution and Bandwidth Enhancement for Limited-Data Photoacoustic Tomography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Photoacoustic tomography (PAT) is a noninvasive imaging modality combining the benefits of optical contrast at ultrasonic resolution. Analytical reconstruction algorithms for photoacoustic (PA) signals require a large number of data points for accura...