Deep-neural-network-based sinogram synthesis for sparse-view CT image reconstruction
Recently, a number of approaches to low-dose computed tomography (CT) have been
developed and deployed in commercialized CT scanners. Tube current reduction is perhaps …
developed and deployed in commercialized CT scanners. Tube current reduction is perhaps …
Sparse-view CT reconstruction based on multi-level wavelet convolution neural network
M Lee, H Kim, HJ Kim - Physica Medica, 2020 - Elsevier
Sparse-view computed tomography (CT) is a recent approach to reducing the radiation dose
in patients and speeding up the data acquisition. Consequently, sparse-view CT has been of …
in patients and speeding up the data acquisition. Consequently, sparse-view CT has been of …
Sinogram interpolation for sparse-view micro-CT with deep learning neural network
In sparse-view Computed Tomography (CT), only a small number of projection images are
taken around the object, and sinogram interpolation method has a significant impact on final …
taken around the object, and sinogram interpolation method has a significant impact on final …
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 …
sparsely collected data or under-sampled measurements, which are practically important for …
3D feature constrained reconstruction for low-dose CT imaging
Low-dose computed tomography (LDCT) images are often highly degraded by amplified
mottle noise and streak artifacts. Maintaining image quality under low-dose scan protocols is …
mottle noise and streak artifacts. Maintaining image quality under low-dose scan protocols is …
View-interpolation of sparsely sampled sinogram using convolutional neural network
Spare-view sampling and its associated iterative image reconstruction in computed
tomography have actively investigated. Sparse-view CT technique is a viable option to low …
tomography have actively investigated. Sparse-view CT technique is a viable option to low …
High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains
Purpose Sparsely sampled computed tomography (CT) has been attracting attention as a
technique that can reduce the high radiation dose of conventional CT. In general, iterative …
technique that can reduce the high radiation dose of conventional CT. In general, iterative …
A sparse-view CT reconstruction method based on combination of DenseNet and deconvolution
Sparse-view computed tomography (CT) holds great promise for speeding up data
acquisition and reducing radiation dose in CT scans. Recent advances in reconstruction …
acquisition and reducing radiation dose in CT scans. Recent advances in reconstruction …
Hybrid-domain neural network processing for sparse-view CT reconstruction
X-ray computed tomography (CT) is one of the most widely used tools in medical imaging,
industrial nondestructive testing, lesion detection, and other applications. However …
industrial nondestructive testing, lesion detection, and other applications. However …
[HTML][HTML] Artifact removal using improved GoogLeNet for sparse-view CT reconstruction
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with
both accelerated scan and reduced projection/back-projection calculation. Despite the rapid …
both accelerated scan and reduced projection/back-projection calculation. Despite the rapid …