Medical image reconstruction aims to acquire high-quality medical images for clinical usage
at minimal cost and risk to the patients. Deep learning and its applications in medical …

Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT)
is a mathematical process that generates images at many different angles around the …

The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …

In medical imaging, accurate diagnosis heavily relies on effective image enhancement
techniques, particularly for X-ray images. Existing methods often suffer from various …

Medical imaging modalities play a crucial part in the process of medical diagnosis. The
medical images such as X-ray, computed tomography (CT), magnetic resonance imaging …

Speckle noise is a commonly known phenomenon for ultrasound imaging systems, which
got introduced due to random interference of coherent waves. The measurement of …

Retinex-based algorithms, drawing inspiration from the human visual system biology, have
emerged as favored techniques in literature for enhancing low-light images. These …

Model or parameter sharing has been commonly used in many distributed learning
architectures, eg, federated learning. However, such a sharing mechanism may result in the …

Biomedical image reconstruction research has been developed for more than five decades,
giving rise to various techniques such as central and filtered back projection. With the rise of …

Abstract In recent times, Artificial Intelligence (AI) attracted many researchers in medical
image analysis. Analyzing the vast medical data through traditional approaches is a bit …