[HTML][HTML] Recent Advances in Photoacoustic Imaging: Current Status and Future Perspectives
H Liu, X Teng, S Yu, W Yang, T Kong, T Liu - Micromachines, 2024 - mdpi.com
Photoacoustic imaging (PAI) is an emerging hybrid imaging modality that combines high-
contrast optical imaging with high-spatial-resolution ultrasound imaging. PAI can provide a …
contrast optical imaging with high-spatial-resolution ultrasound imaging. PAI can provide a …
Deep embedding-attention-refinement for sparse-view CT reconstruction
Tomographic image reconstruction with deep learning is an emerging field of applied
artificial intelligence. Reducing radiation dose with sparse views' reconstruction is a …
artificial intelligence. Reducing radiation dose with sparse views' reconstruction is a …
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 …
Iterative residual optimization network for limited-angle tomographic reconstruction
Limited-angle tomographic reconstruction is one of the typical ill-posed inverse problems,
leading to edge divergence with degraded image quality. Recently, deep learning has been …
leading to edge divergence with degraded image quality. Recently, deep learning has been …
Time-reversion fast-sampling score-based model for limited-angle CT reconstruction
Y Wang, Z Li, W Wu - IEEE Transactions on Medical Imaging, 2024 - ieeexplore.ieee.org
The score-based generative model (SGM) has received significant attention in the field of
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
Low-dose CT image synthesis for domain adaptation imaging using a generative adversarial network with noise encoding transfer learning
M Li, J Wang, Y Chen, Y Tang, Z Wu… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Deep learning (DL) based image processing methods have been successfully applied to
low-dose x-ray images based on the assumption that the feature distribution of the training …
low-dose x-ray images based on the assumption that the feature distribution of the training …
CCN-CL: A content-noise complementary network with contrastive learning for low-dose computed tomography denoising
Y Tang, Q Du, J Wang, Z Wu, Y Li, M Li, X Yang… - Computers in Biology …, 2022 - Elsevier
In recent years, low-dose computed tomography (LDCT) has played an increasingly
important role in the diagnosis CT to reduce the potential adverse effects of x-ray radiation …
important role in the diagnosis CT to reduce the potential adverse effects of x-ray radiation …
[HTML][HTML] Fast and low-dose medical imaging generation empowered by hybrid deep-learning and iterative reconstruction
S Liao, Z Mo, M Zeng, J Wu, Y Gu, G Li, G Quan… - Cell Reports …, 2023 - cell.com
Fast and low-dose reconstructions of medical images are highly desired in clinical routines.
We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework …
We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework …
A two-branch neural network for short-axis PET image quality enhancement
The axial field of view (FOV) is a key factor that affects the quality of PET images. Due to
hardware FOV restrictions, conventional short-axis PET scanners with FOVs of 20 to 35 cm …
hardware FOV restrictions, conventional short-axis PET scanners with FOVs of 20 to 35 cm …
PIE-ARNet: Prior image enhanced artifact removal network for limited-angle DECT
Dual-energy computed tomography (DECT) is of great clinical significance because it can
simultaneously visualize the internal structure of the scanned object and provide material …
simultaneously visualize the internal structure of the scanned object and provide material …