Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …

Image reconstruction is an inverse problem that solves for a computational image based on
sampled sensor measurement. Sparsely sampled image reconstruction poses additional …

This paper proposes a novel and fast self-supervised solution for sparse-view CBCT
reconstruction (Cone Beam Computed Tomography) that requires no external training data …

X-ray known for its ability to reveal internal structures of objects is expected to provide richer
information for 3D reconstruction than visible light. Yet existing NeRF algorithms overlook …

A generative adversarial network (GAN) is one of the most significant research directions in
the field of artificial intelligence, and its superior data generation capability has garnered …

Generative Adversarial Networks (GANs) have achieved impressive results in various image
synthesis tasks, and are becoming a hot topic in computer vision research because of the …

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread
rapidly since December 2019. Real-time reverse transcription polymerase chain reaction …

Computed tomography (CT) is an effective med-ical imaging modality, widely used in the
field of clinical medicine for the diagnosis of various pathologies. Advances in Multidetector …

Artificial intelligence (AI)-based technologies are actively used for purposes of cyber
defense. With the passage of time and with decreasing complexity in implementing AI-based …