Search Results for author:
Found 5 papers, 1 papers with code
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
Given the potential X-ray radiation risk to the patient, low-dose CT has attracted a considerable interest in the medical imaging field.
LEARN: Learned Experts' Assessment-based Reconstruction Network for Sparse-data CT
Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-view CT, tomosynthesis, interior tomography, and so on.
Low-dose CT denoising with convolutional neural network
To reduce the potential radiation risk, low-dose CT has attracted much attention.
Low-Dose CT via Deep Neural Network
In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention.
Medical Physics
Visual Attention Network for Low Dose CT
Noise and artifacts are intrinsic to low dose CT (LDCT) data acquisition, and will significantly affect the imaging performance.
