Recent advances of transformers in medical image analysis: a comprehensive review
K Xia, J Wang - MedComm–Future Medicine, 2023 - Wiley Online Library
Recent works have shown that Transformer's excellent performances on natural language
processing tasks can be maintained on natural image analysis tasks. However, the …
processing tasks can be maintained on natural image analysis tasks. However, the …
A self-supervised guided knowledge distillation framework for unpaired low-dose CT image denoising
J Wang, Y Tang, Z Wu, Q Du, L Yao, X Yang… - … medical imaging and …, 2023 - Elsevier
Low-dose computed tomography (LDCT) can significantly reduce the damage of X-ray to the
human body, but the reduction of CT dose will produce images with severe noise and …
human body, but the reduction of CT dose will produce images with severe noise and …
Diffusion probabilistic priors for zero-shot low-dose ct image denoising
Denoising low-dose computed tomography (CT) images is a critical task in medical image
computing. Supervised deep learning-based approaches have made significant …
computing. Supervised deep learning-based approaches have made significant …
CT image denoising methods for image quality improvement and radiation dose reduction
With the ever‐increasing use of computed tomography (CT), concerns about its radiation
dose have become a significant public issue. To address the need for radiation dose …
dose have become a significant public issue. To address the need for radiation dose …
Synthetic CT generation based on CBCT using improved vision transformer CycleGAN
Y Hu, H Zhou, N Cao, C Li, C Hu - Scientific Reports, 2024 - nature.com
Cone-beam computed tomography (CBCT) is a crucial component of adaptive radiation
therapy; however, it frequently encounters challenges such as artifacts and noise …
therapy; however, it frequently encounters challenges such as artifacts and noise …
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation
Deep learning models for medical image segmentation and object detection are becoming
increasingly available as clinical products. However, as details are rarely provided about the …
increasingly available as clinical products. However, as details are rarely provided about the …
XGenRecon: A New Perspective in Ultra-Sparse Volumetric CBCT Reconstruction Through Geometry-Controlled X-ray Projection Generation
We propose a novel paradigm for cone-beam computed tomography (CBCT) reconstruction
from ultra-sparse X-ray projections, by introducing a framework that generates auxiliary X …
from ultra-sparse X-ray projections, by introducing a framework that generates auxiliary X …
Psdp: Pseudo-supervised dual-processing for low-dose cone-beam computed tomography reconstruction
L Chao, W Shan, Y Wang, W Xu, H Zhang… - Expert Systems with …, 2023 - Elsevier
Low-dose cone-beam computed tomography (CBCT) is reconstructed from hundreds of 2D
X-ray projections of low intensity to reduce ionizing radiation to patients, but its imaging …
X-ray projections of low intensity to reduce ionizing radiation to patients, but its imaging …
WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT Denoising
In clinical examinations and diagnoses, low-dose computed tomography (LDCT) is crucial
for minimizing health risks compared with normal-dose computed tomography (NDCT) …
for minimizing health risks compared with normal-dose computed tomography (NDCT) …
Rethinking Low-Dose CT Synthesis: Degrading Normal-Dose CT from Origin for Pairwise Training of CT Denoiser
L Chao, T Zhang, Y Wang, W Shan… - … on Bioinformatics and …, 2023 - ieeexplore.ieee.org
Training a denoiser for translating low-dose to normal-dose computed tomography (LDCT to
NDCT) requires collecting spatially corresponded paired data, yet it is impractical. Existing …
NDCT) requires collecting spatially corresponded paired data, yet it is impractical. Existing …