Domain progressive 3D residual convolution network to improve low-dose CT imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
Low-dose CT denoising via sinogram inner-structure transformer
Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to
human bodies, is now attracting increasing interest in the medical imaging field. As the …
human bodies, is now attracting increasing interest in the medical imaging field. As the …
Directional-TV algorithm for image reconstruction from limited-angular-range data
Investigation of image reconstruction from data collected over a limited-angular range in X-
ray CT remains a topic of active research because it may yield insight into the development …
ray CT remains a topic of active research because it may yield insight into the development …
Non-convex primal-dual algorithm for image reconstruction in spectral CT
The work seeks to develop an algorithm for image reconstruction by directly inverting the
non-linear data model in spectral CT. Using the non-linear data model, we formulate the …
non-linear data model in spectral CT. Using the non-linear data model, we formulate the …
Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT
Optimization-based algorithms for image reconstruction in multispectral (or photon-counting)
computed tomography (MCT) remains a topic of active research. The challenge of …
computed tomography (MCT) remains a topic of active research. The challenge of …
A cone-beam X-ray computed tomography data collection designed for machine learning
Unlike previous works, this open data collection consists of X-ray cone-beam (CB) computed
tomography (CT) datasets specifically designed for machine learning applications and high …
tomography (CT) datasets specifically designed for machine learning applications and high …
4D-image reconstruction directly from limited-angular-range data in continuous-wave electron paramagnetic resonance imaging
Objective: We investigate and develop optimization-based algorithms for accurate
reconstruction of four-dimensional (4D)-spectral-spatial (SS) images directly from data …
reconstruction of four-dimensional (4D)-spectral-spatial (SS) images directly from data …
Tomographic reconstruction: General approach to fast back-projection algorithms
Addressing contemporary challenges in computed tomography (CT) demands precise and
efficient reconstruction. This necessitates the optimization of CT methods, particularly by …
efficient reconstruction. This necessitates the optimization of CT methods, particularly by …
Adversarial sparse-view CBCT artifact reduction
We present an effective post-processing method to reduce the artifacts from sparsely
reconstructed cone-beam CT (CBCT) images. The proposed method is based on the state-of …
reconstructed cone-beam CT (CBCT) images. The proposed method is based on the state-of …
Are metal artefact reduction algorithms effective to correct cone beam CT artefacts arising from the exomass?
The aim of this study was to evaluate the effectiveness of metal artefact reduction (MAR) in
cone beam CT (CBCT) artefacts arising from metallic objects in the exomass. A radiographic …
cone beam CT (CBCT) artefacts arising from metallic objects in the exomass. A radiographic …