[HTML][HTML] SYNAPSE: An international roadmap to large brain imaging
APJ Stampfl, Z Liu, J Hu, K Sawada, H Takano… - Physics Reports, 2023 - Elsevier
Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
A Systematic Literature Review of 3D Deep Learning Techniques in Computed Tomography Reconstruction
Computed tomography (CT) is used in a wide range of medical imaging diagnoses.
However, the reconstruction of CT images from raw projection data is inherently complex …
However, the reconstruction of CT images from raw projection data is inherently complex …
Deep cascade residual networks (DCRNs): optimizing an encoder–decoder convolutional neural network for low-dose CT imaging
To suppress noise and artifacts caused by the reduced radiation exposure in low-dose
computed tomography, several deep learning (DL)-based image restoration methods have …
computed tomography, several deep learning (DL)-based image restoration methods have …
Physics-/model-based and data-driven methods for low-dose computed tomography: A survey
Since 2016, deep learning (DL) has advanced tomographic imaging with remarkable
successes, especially in low-dose computed tomography (LDCT) imaging. Despite being …
successes, especially in low-dose computed tomography (LDCT) imaging. Despite being …
Self-supervised deep image restoration via adaptive stochastic gradient langevin dynamics
While supervised deep learning has been a prominent tool for solving many image
restoration problems, there is an increasing interest on studying self-supervised or un …
restoration problems, there is an increasing interest on studying self-supervised or un …
[PDF][PDF] 基于特征融合的非局部均值CT 图像降噪
龙超， 金恒， 黎玲， 盛晋银， 段黎明 - 光学学报, 2022 - researching.cn
摘要针对现有非局部均值算法降噪后的计算机断层扫描(CT) 图像仍存在边缘模糊,
细小特征信息消失等问题, 提出一种特征融合的自适应非局部均值降噪方法 …
细小特征信息消失等问题, 提出一种特征融合的自适应非局部均值降噪方法 …
Deep residual constrained reconstruction via learned convolutional sparse coding for low-dose CT imaging
Low-dose computed tomography (LDCT) holds great potential to reduce radiation dose
damage. However, LDCT degrades the signal-to-noise ratio (SNR) of projection and …
damage. However, LDCT degrades the signal-to-noise ratio (SNR) of projection and …
Modal adaptive super-resolution for medical images via continual learning
Details related to tiny abnormal pathologies and textures are crucial for clinical experts and
computer-aided diagnosis in medical imaging. Super-resolving medical images provide …
computer-aided diagnosis in medical imaging. Super-resolving medical images provide …
An optimized EBRSA-Bi LSTM model for highly undersampled rapid CT image reconstruction
AVP Sarvari, K Sridevi - Biomedical Signal Processing and Control, 2023 - Elsevier
COVID-19 has spread all over the world, causing serious panic around the globe. Chest
computed tomography (CT) images are integral in confirming COVID positive patients …
computed tomography (CT) images are integral in confirming COVID positive patients …
[HTML][HTML] Attention-based dual-branch deep network for sparse-view computed tomography image reconstruction
X Gao, T Su, Y Zhang, J Zhu, Y Tan, H Cui… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background The widespread application of X-ray computed tomography (CT) imaging in
medical screening makes radiation safety a major concern for public health. Sparse-view CT …
medical screening makes radiation safety a major concern for public health. Sparse-view CT …