Typically, a medical image offers spatial information on the anatomy (and pathology)
modulated by imaging specific characteristics. Many imaging modalities including Magnetic …

Bone marrow adipose tissue (BMAT) comprises >10% of total adipose mass, yet unlike white
or brown adipose tissues (WAT or BAT) its metabolic functions remain unclear. Herein, we …

Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-domain
medical image synthesis tasks particularly due to its ability to deal with unpaired …

In modern Internet of Things (IoT), visual analysis and predictions are often performed by deep
learning models. Salient object detection (SOD) is a fundamental preprocessing for these …

The success and generalisation of deep learning algorithms heavily depend on learning
good feature representations. In medical imaging this entails representing anatomical …

Magnetic resonance (MR) protocols rely on several sequences to assess pathology and
organ status properly. Despite advances in image analysis, we tend to treat each sequence, …

Purpose: To examine whether ultra-widefield (UWF) retinal imaging can identify biomarkers
for Alzheimer’s disease (AD) and its progression. Methods: Images were taken using a UWF …

Deep convoloutional networks have been widely deployed in modern cyber-physical systems
performing different visual classification tasks. As the fog and edge devices have different …

Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …

A drug delivery nanosystem of noble bimetallic nanoparticles (NPs) which consists of Au
NPs capped with Pt NPs (Au@Pt NPs) is constructed and functionalised with a quinazoline …