Deep learning is having a profound impact in many fields, especially those that involve some form of image processing. Deep neural networks excel in turning an input image into a set of high-level features. On the other hand, tomography deals with the inverse problem of recreating an image from a number of projections. In plasma diagnostics, tomography aims at reconstructing the cross-section of the plasma from radiation measurements. This reconstruction can be computed with neural networks. However, previous attempts have focused on learning a parametric model of the plasma profile. In this work, we use a deep neural network to produce a full, pixel-by-pixel reconstruction of the plasma profile. For this purpose, we use the overview bolome...
Bolometric tomography is a widely applied technique to infer important indirect quantities in magnet...
The diagnosis of plasma cell neoplasms requires accurate, and ideally precise, percentages. This pla...
In this article, we introduce three different strategies of tomographic reconstruction based on deep...
Deep learning is having a profound impact in many fields, especially those that involve some form of...
Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as...
Plasma tomography consists of reconstructing a two-dimensional radiation profile of a poloidal cross...
Image reconstruction for positron emission tomography (PET) is challenging because of the ill-condit...
The aim of this research is towards creating superior algorithms for Positron Emission Tomography (P...
Image reconstruction for positron emission tomography (PET) is challenging because of the ill-condit...
Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such...
Proton radiography is a technique extensively used to resolve magnetic field structures in high-ener...
This study investigates the possibility of using an Artificial Neural Network (ANN) for reconstructi...
We investigate the usage of a Schlieren imaging setup to measure the geometrical dimensions of a pla...
We accurately reconstruct three-dimensional (3-D) refractive index (RI) distributions from highly il...
This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm...
Bolometric tomography is a widely applied technique to infer important indirect quantities in magnet...
The diagnosis of plasma cell neoplasms requires accurate, and ideally precise, percentages. This pla...
In this article, we introduce three different strategies of tomographic reconstruction based on deep...
Deep learning is having a profound impact in many fields, especially those that involve some form of...
Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as...
Plasma tomography consists of reconstructing a two-dimensional radiation profile of a poloidal cross...
Image reconstruction for positron emission tomography (PET) is challenging because of the ill-condit...
The aim of this research is towards creating superior algorithms for Positron Emission Tomography (P...
Image reconstruction for positron emission tomography (PET) is challenging because of the ill-condit...
Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such...
Proton radiography is a technique extensively used to resolve magnetic field structures in high-ener...
This study investigates the possibility of using an Artificial Neural Network (ANN) for reconstructi...
We investigate the usage of a Schlieren imaging setup to measure the geometrical dimensions of a pla...
We accurately reconstruct three-dimensional (3-D) refractive index (RI) distributions from highly il...
This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm...
Bolometric tomography is a widely applied technique to infer important indirect quantities in magnet...
The diagnosis of plasma cell neoplasms requires accurate, and ideally precise, percentages. This pla...
In this article, we introduce three different strategies of tomographic reconstruction based on deep...