At the beginning of the COVID-19 pandemic, there was significant hype about the potential
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …

Quantum state tomography (QST) is a challenging task in intermediate-scale quantum
devices. Here, we apply conditional generative adversarial networks (CGANs) to QST. In the …

Radiomic approaches in precision medicine are promising, but variation associated with
image acquisition factors can result in severe biases and low generalizability. Multicenter …

Currently, medical image domain translation operations show a high demand from
researchers and clinicians. Amongst other capabilities, this task allows the generation of …

High-quality image reconstruction is essential for many electrical capacitance tomography
(CT) applications. Raw capacitance measurements are used in the literature to generate low …

Magnetic resonance imaging (MRI) provides enhanced soft tissue contrast and high spatial
resolution. However, the relationship between intensity values among soft tissues in MRI is …

Computed tomography (CT) is one of the modalities for effective lung cancer screening,
diagnosis, treatment, and prognosis. The features extracted from CT images are now used to …

While remarkable advances have been made in Computed Tomography (CT), most of the
existing efforts focus on imaging enhancement while reducing radiation dose. How to …

While remarkable advances have been made in Computed Tomography (CT), most of the
existing efforts focus on imaging enhancement while reducing radiation dose. How to …

Automatic medical image segmentation is a crucial procedure for computer-assisted
surgery. Especially, three-dimensional reconstruction of medical images of the surgical …