Untrained Physically Informed Neural Network for Image Reconstruction of Magnetic Field Sources

A Radon-based Convolutional Neural Network for Medical Image Retrieval

Image classification and retrieval systems have gained more attention because of easier access to high-tech medical imaging. However, the lack of availability of large-scaled balanced labelled data in medicine is still a challenge. Simplicity, practicality, efficiency, and effectiveness are the main targets in medical domain. To achieve these goals, Radon transformation, which is a well-known t...

Reconstruction of Solar Coronal Linear Force-Free Magnetic Field

Physically Trained and Untrained Humans

The purpose of this study was to determine if the state of physical training influences sympathetic neural activation during acute stress in humans. We recorded muscle sympathetic nerve activity (microneurography of the peroneal nerve), arterial blood pressure, and heart rate in 12 highly trained, endurance athletes (25 ±1 years, mean±SEM) and 12 untrained subjects (27±1 years) before (supine r...

A neural network image reconstruction technique for electrical impedance tomography

Reconstruction of images in electrical impedance tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. The authors present a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse pr...

Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images

Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...