A wavelet-based sparsity-promoting reconstruction method is studied in the context of tomography with severely limited projection data.

Sparse-view has been widely studied as a potential strategy. Compressed sensing (CS) method has shown great potential to reconstruct high-quality CT images from ...

Dec 25, 2023 · Abstract:Sparse-view CT is a promising strategy for reducing the radiation dose of traditional CT scans, but reconstructing high-quality ...

Their physics-aware deep learning framework is able to reconstruct high quality MRI from sparse k-space samples, and they have validated the proposed approach ...

Jun 5, 2013 · The sparse-view CT refers to CT in which measured number of projection data is reduced to less than 100 determined by applications and required ...

Oct 25, 2021 · We have developed a sparse imaging and reconstruction tomography (SMART) system that allows brain-wide imaging of cortical projection neurons at synaptic ...

May 22, 2020 · It was shown capable of achieving comparable or better performance than iterative methods for limited-view and sparse PAT image reconstruction.

Jun 24, 2024 · DIP achieves sparse representation and dimensionality reduction of images by jointly using the convolutional kernels and network layers.

Nov 12, 2019 · Sparse-view tomography has many applications such as in low-dose computed tomography (CT). Using under-sampled data, a perfect image is not ...

This sparse CT reconstruction method involves constructing and minimizing an energy model, which comprises both a data fidelity term and a regularization term.