Systematic review on learning-based spectral CT
Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
Artificial intelligence in functional imaging of the lung
R San José Estépar - The British Journal of Radiology, 2022 - academic.oup.com
Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-
resolution image reconstruction to predicting functional response from clinically acquired …
resolution image reconstruction to predicting functional response from clinically acquired …
Synthetic data in healthcare
Synthetic data are becoming a critical tool for building artificially intelligent systems.
Simulators provide a way of generating data systematically and at scale. These data can …
Simulators provide a way of generating data systematically and at scale. These data can …
Sim2real transfer learning for point cloud segmentation: An industrial application case on autonomous disassembly
On robotics computer vision tasks, generating and annotating large amounts of data from
real-world for the use of deep learning-based approaches is often difficult or even …
real-world for the use of deep learning-based approaches is often difficult or even …
Feasibility study of three-material decomposition in dual-energy cone-beam CT imaging with deep learning
J Zhu, T Su, X Zhang, J Yang, D Mi… - Physics in Medicine …, 2022 - iopscience.iop.org
Objective. In this work, a dedicated end-to-end deep convolutional neural network, named
as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different …
as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different …
Deep learning‐based virtual noncalcium imaging in multiple myeloma using dual‐energy CT
Background Dual‐energy CT with virtual noncalcium (VNCa) images allows the evaluation
of focal intramedullary bone marrow involvement in patients with multiple myeloma …
of focal intramedullary bone marrow involvement in patients with multiple myeloma …
Material decomposition from photon-counting CT using a convolutional neural network and energy-integrating CT training labels
Objective. Photon-counting CT (PCCT) has better dose efficiency and spectral resolution
than energy-integrating CT, which is advantageous for material decomposition …
than energy-integrating CT, which is advantageous for material decomposition …
Addressing data imbalance in Sim2Real: ImbalSim2Real scheme and its application in finger joint stiffness self-sensing for soft robot-assisted rehabilitation
The simulation-to-reality (sim2real) problem is a common issue when deploying simulation-
trained models to real-world scenarios, especially given the extremely high imbalance …
trained models to real-world scenarios, especially given the extremely high imbalance …
Virtual computed-tomography system for deep-learning-based material decomposition
D Fujiwara, T Shimomura, W Zhao, KW Li… - Physics in Medicine …, 2022 - iopscience.iop.org
Objective. Material decomposition (MD) evaluates the elemental composition of human
tissues and organs via computed tomography (CT) and is indispensable in correlating …
tissues and organs via computed tomography (CT) and is indispensable in correlating …
Improving Spectral CT Image Quality Based on Channel Correlation and Self-Supervised Learning
Photon counting spectral computed tomography (PCCT) can produce reconstructed
attenuation maps in different energy channels, reflecting the energy properties of the …
attenuation maps in different energy channels, reflecting the energy properties of the …