The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …

Recent years have witnessed a significant advancement in brain imaging techniques that
offer a non-invasive approach to map** the structure and function of the brain …

In this paper, the fractal calculus is introduced to study a non-smooth boundary layer of a
viscous fluid, and a fractal-fractional modification of the Blasius equation is suggested and …

In recent years, deep learning super-resolution models for progressive reconstruction have
achieved great success. However, these models which refer to multi-resolution analysis …

In current study, the modified variational iteration algorithm-I is investigated in the form of the
analytical and numerical treatment of different types of nonlinear partial differential …

The state-of-the-art deep learning methods have demonstrated impressive performance in
segmentation tasks. However, the success of these methods depends on a large amount of …

Alzheimer's disease (AD) is characterized by alterations of the brain's structural and
functional connectivity during its progressive degenerative processes. Existing auxiliary …

The ability to translate medical images across different modalities is crucial for synthesizing
missing data and aiding in clinical diagnosis. However, existing learning-based techniques …

Vignetting commonly occurs as a degradation in images resulting from factors such as lens
design, improper lens hood usage, and limitations in camera sensors. This degradation …

Current multi-contrast MRI super-resolution (SR) methods often harness convolutional
neural networks (CNNs) for feature extraction and fusion. However, existing models have …