Purpose Micron-scale computed tomography (micro-CT) imaging is a ubiquitous, cost-
effective, and non-invasive three-dimensional imaging modality. We review recent …

Innovations in CT have been impressive among imaging and medical technologies in both
the hardware and software domain. The range and speed of CT scanning improved from the …

Deep learning has attracted rapidly increasing attention in the field of tomographic image
reconstruction, especially for CT, MRI, PET/SPECT, ultrasound and optical imaging. Among …

X-ray computed tomography (CT) using sparse projection views is a recent approach to
reduce the radiation dose. However, due to the insufficient projection views, an analytic …

Purpose Due to the potential risk of inducing cancer, radiation exposure by X‐ray CT
devices should be reduced for routine patient scanning. However, in low‐dose X‐ray CT …

Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in
clinical applications. Iterative reconstruction algorithms are one of the most promising way to …

Purpose: A computational toolkit (spektr 3.0) has been developed to calculate x‐ray spectra
based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) …

Purpose A new acquisition and reconstruction method called T2 Shuffling is presented for
volumetric fast spin‐echo (three‐dimensional [3D] FSE) imaging. T2 Shuffling reduces …

Motivated by the great potential of deep learning in medical imaging, we propose an
iterative positron emission tomography reconstruction framework using a deep learning …

Reducing the exposure to X-ray radiation while maintaining a clinically acceptable image
quality is desirable in various CT applications. To realize low-dose CT (LdCT) imaging …