A review on medical imaging synthesis using deep learning and its clinical applications
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …
clinical application. Specifically, we summarized the recent developments of deep learning …
A survey on deep learning in medical image reconstruction
E Ahishakiye, M Bastiaan Van Gijzen… - Intelligent …, 2021 - mednexus.org
Medical image reconstruction aims to acquire high-quality medical images for clinical usage
at minimal cost and risk to the patients. Deep learning and its applications in medical …
at minimal cost and risk to the patients. Deep learning and its applications in medical …
CLEAR: comprehensive learning enabled adversarial reconstruction for subtle structure enhanced low-dose CT imaging
X-ray computed tomography (CT) is of great clinical significance in medical practice
because it can provide anatomical information about the human body without invasion …
because it can provide anatomical information about the human body without invasion …
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 …
Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks
Introduction The purpose of this work was to assess the feasibility of acquisition time
reduction in MPI-SPECT imaging using deep leering techniques through two main …
reduction in MPI-SPECT imaging using deep leering techniques through two main …
Limited view tomographic reconstruction using a cascaded residual dense spatial-channel attention network with projection data fidelity layer
Limited view tomographic reconstruction aims to reconstruct a tomographic image from a
limited number of projection views arising from sparse view or limited angle acquisitions that …
limited number of projection views arising from sparse view or limited angle acquisitions that …
Coil: Coordinate-based internal learning for imaging inverse problems
We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL)
methodology for the continuous representation of measurements. Unlike traditional DL …
methodology for the continuous representation of measurements. Unlike traditional DL …
Data extrapolation from learned prior images for truncation correction in computed tomography
Data truncation is a common problem in computed tomography (CT). Truncation causes
cupping artifacts inside the field-of-view (FOV) and anatomical structures missing outside the …
cupping artifacts inside the field-of-view (FOV) and anatomical structures missing outside the …
System and method for multi-architecture computed tomography pipeline
A system and method for reconstructing an image of a subject acquired using a tomographic
imaging system includes at least one computer processor configured to form an image …
imaging system includes at least one computer processor configured to form an image …
Accurate and robust sparse‐view angle CT image reconstruction using deep learning and prior image constrained compressed sensing (DL‐PICCS)
Background: Sparse‐view CT image reconstruction problems encountered in dynamic CT
acquisitions are technically challenging. Recently, many deep learning strategies have been …
acquisitions are technically challenging. Recently, many deep learning strategies have been …