Deep learning for tomographic image reconstruction
Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
[HTML][HTML] A gentle introduction to deep learning in medical image processing
This paper tries to give a gentle introduction to deep learning in medical image processing,
proceeding from theoretical foundations to applications. We first discuss general reasons for …
proceeding from theoretical foundations to applications. We first discuss general reasons for …
Solving inverse problems in medical imaging with score-based generative models
Reconstructing medical images from partial measurements is an important inverse problem
in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions …
in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions …
NeRP: implicit neural representation learning with prior embedding for sparsely sampled image reconstruction
Image reconstruction is an inverse problem that solves for a computational image based on
sampled sensor measurement. Sparsely sampled image reconstruction poses additional …
sampled sensor measurement. Sparsely sampled image reconstruction poses additional …
Image reconstruction is a new frontier of machine learning
Over past several years, machine learning, or more generally artificial intelligence, has
generated overwhelming research interest and attracted unprecedented public attention. As …
generated overwhelming research interest and attracted unprecedented public attention. As …
DOLCE: A model-based probabilistic diffusion framework for limited-angle ct reconstruction
Abstract Limited-Angle Computed Tomography (LACT) is a non-destructive 3D imaging
technique used in a variety of applications ranging from security to medicine. The limited …
technique used in a variety of applications ranging from security to medicine. The limited …
Learning to reconstruct computed tomography images directly from sinogram data under a variety of data acquisition conditions
Computed tomography (CT) is widely used in medical diagnosis and non-destructive
detection. Image reconstruction in CT aims to accurately recover pixel values from measured …
detection. Image reconstruction in CT aims to accurately recover pixel values from measured …
Deep learning for massive MIMO uplink detectors
MA Albreem, AH Alhabbash… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of
attention in both academia and industry. Detection techniques have a significant impact on …
attention in both academia and industry. Detection techniques have a significant impact on …
Coil: Coordinate-based internal learning for tomographic imaging
We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL)
methodology for continuous representation of measurements. Unlike traditional DL methods …
methodology for continuous representation of measurements. Unlike traditional DL methods …
Radon inversion via deep learning
The Radon transform is widely used in physical and life sciences, and one of its major
applications is in medical X-ray computed tomography (CT), which is significantly important …
applications is in medical X-ray computed tomography (CT), which is significantly important …